• опыт классического ML на табличных данных (скоринг, антифрод, рекомендательные системы, прогноз спроса или оттока, ценообразование и похожие задачи). • Python (pandas, numpy).
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• опыт классического ML на табличных данных (скоринг, антифрод, рекомендательные системы, прогноз спроса или оттока, ценообразование и похожие задачи). • Python (pandas, numpy).
Location: Москва ИТ B2C — самая крупная экосистема в Сбере. Нас более 8000 человек в 18 городах России. Мы занимаемся разработкой и развитием розничных решений, помогая сделать сервисы Банка доступнее, безопаснее и удобнее. Обеспеченное будущее позволит клиенту использовать инструменты финансового планирования для формирования долгосрочных планов на периоде 10+ лет. Проект позволит формировать план финансовой независимости и отслеживать его достижение и текущий статус, а также будет проактивно давать совету по его улучшению и минимизации рисков. Обязанности * анализ дефектов, инцидентов и их классификация * контроль качества продукта на всех этапах жизненного цикла * функциональное, регрессионное, интеграционное тестирование * участие в приемно-сдаточных испытаниях * контроль за процессом релиза * разработка и актуализация тестовых планов, написание тестов по новым фичам * помощь разработчикам в локализации и решении проблем Требования * коммерческий опыт в тестировании от 2-х лет * опыт использования методологий оптимизации наборов тестовых данных, применения AI-агентов в процессе тестирования * опыт работы с REST API, gRPC, Kafka, системами управления тестированием (TM4J, Test IT, TestRail, MS TFS) * понимание принципов работы протоколов HTTPS / HTTP * опыт автотестирования на Java * понимание теоретических основ AI и ML: принципов работы нейронных сетей, обучения моделей (включая NLP и компьютерное зрение), навыки анализа качества данных и знание специфических метрик оценки (Precision, Recall, F1-Score, Accuracy, Confusion Matrix, IOU) Условия * формат работы - гибрид (БЦ Поклонка) * ежегодный пересмотр зарплаты и годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * бесплатная подписка СберПрайм с возможностью совместного использования на трех близких, скидки на продукты компаний-партнеров * вознаграждение за рекомендацию друзей в команду Сбера * корпоративная пенсионная программа.
Location: Москва Мы исследовательское подразделение, которое отвечает в Сбере за «человека»: поведение, психология, тренды, изменения, особенности восприятия и мышления. Наша ключевая задача: исследовать и рассказывать, что происходит и будет происходить с человеком, как эти изменения переложить в продукт, коммуникации, HR-процессы, чтобы они стали лучше. Работа в Лаборатории – это возможность прикоснуться практически к любому бизнес-подразделению экосистемы Сбера, к большим данным Сбера, к клиентской базе более 100 млн человек. Мы ищем ML Developer'а — человека, который будет реализовывать ML-проекты Лаборатории: обучение и дообучение моделей, построение data-пайплайнов, вывод решений в production. В отличие от LLM-генералистов команды, которые быстро вайбкодят прототипы, вы будете отвечать за то, чтобы модели работали надёжно, воспроизводимо и масштабируемо, а также дорабатывать прототипы до продакшен решений. Вы рамках Лаборатории вы будете в команде “больших данных и гиперперсонализации”, всего около 25 человек, из которых DS-команда – порядка 10 человек, остальные – исследователи, психологи и социологи. Лаборатория работает на стыке поведенческой науки, данных и AI. Мы строим модели, которые описывают и предсказывают поведение человека — от сегментации клиентов до цифровых двойников. ML Developer — это тот, кто превращает исследовательские гипотезы в работающие модели и надёжную инфраструктуру вокруг них. Наш технологический стек: * ML/DL: HuggingFace Transformers, SentenceTransformers, CatBoost, XGBoost * LLM & Vector Search: локальные модели (Llama 3, Qwen), API (OpenAI), FAISS * Data & Infra: ClickHouse, Docker, FastAPI, Postgres, RabbitMQ, MongoDB * MLOps & Orchestration: MLflow, W&B, Prefect, Dagster, Ray, Prometheus, OpenTelemetry * Инструменты: Hydra, Poetry. Первый этап отбора на эту вакансию – общение с AI-рекрутером. После отклика ждите сообщение от него в мессенджере, диалог займёт примерно 10 минут. Задача AI-рекрутера — уточнить недостающие детали и ускорить рассмотрение вашей кандидатуры. AI-рекрутер только начинает свой путь, поэтому просим относиться с пониманием. Ваш опыт и участие помогут сделать его удобным и полезным для всех! Обязанности ### Чем предстоит заниматься: * классический ML/NLP: разработка и обучение моделей для анализа текстов, поведенческих данных, психометрических профилей. * кластеризация, классификация, NER, sentiment — всё, что требуется для исследований на данных. * LLM-интеграция: fine-tuning и дообучение языковых моделей под задачи Лаборатории, построение embedding-пайплайнов, проектирование RAG-архитектур с графовыми и векторными БД. * работа с промптами на уровне системной архитектуры, а не ad hoc экспериментов * Production & MLOps: вывод моделей из ноутбуков в production — контейнеризация, CI/CD, мониторинг, версионирование моделей и данных * построение воспроизводимых пайплайнов обработки данных. Требования ### Наши ожидания от кандидата: ML & NLP: * практический опыт обучения и дообучения моделей (классический ML + deep learning) * уверенная работа с NLP: text classification, NER, embeddings, topic modeling, умение работать с ASR, Text-to-Speech задачами * опыт fine-tuning трансформерных моделей (HuggingFace Transformers, PEFT, LoRA, QLoRA) * понимание метрик качества моделей и умение проектировать эксперименты. LLM & Retrieval-архитектуры: * опыт работы с LLM API (OpenAI, Anthropic и др.) на уровне production-решений * построение RAG-пайплайнов: chunking-стратегии, embedding-модели, векторные и графовые БД * понимание различий между векторным поиском и BM25 * работа с LangChain / LangGraph или аналогами. Engineering & MLOps: * Python как основной язык, уверенное владение * Docker, CI/CD, базовый DevOps * опыт работы с ML-оркестраторами (MLflow, W&B, Prefect, Dagster — хотя бы один) * навыки разработки API (FastAPI / аналоги) * работа с SQL-базами (ClickHouse, Postgres) и очередями (RabbitMQ и т.п.). Софты и майндсет: * техническое образование (ML, CS, математика, инженерия) * умение переводить абстрактные исследовательские гипотезы в формализованные ML-задачи * способность объяснять технические решения нетехнической аудитории (исследователям, бизнесу) * интерес к поведенческой науке, психологии — или хотя бы готовность погружаться. Будет плюсом: * опыт работы с распределёнными вычислениями (Ray, DeepSpeed) * знакомство с Prometheus, OpenTelemetry, observability-стеком * опыт работы с графовыми базами данных (Neo4j и т.п.) * контроль стоимости и latency AI-вызовов * публикации, pet-проекты, вклад в open-source * опыт использования GigaChat, Kandinsky и аналогов в продуктах, навыки создания и использования AI-агентов. Условия ### Мы предлагаем: * комфортный современный офис г. Москва, рядом с метро Кутузовская * офисный формат работы: 5/2 с 10 до 19, возможен гибрид (1-2 дня в неделю вне офиса) * ежегодный пересмотр зарплаты и годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера.
Location: Москва **GigaChat увидит мир через данные, которые соберёте вы.** За GigaChat стоит одна из крупнейших ML-команд в России, которая обучает LLM и VLM полным циклом — от претрейна до релиза. Наша команда отвечает за то, с чего начинается любая сильная модель, — за данные: мы собираем визуальный корпус претрейна — ищем источники, фильтруем и дедуплицируем сырьё, ставим эксперименты и меряем влияние на бенчмарки. Именно состав и качество претрейн-данных определяют, каким получится финальный результат, и у вас будет возможность влиять на него напрямую. Обязанности * ставить эксперименты: формулировать гипотезы, какие данные и в каких пропорциях улучшат модель, и проверять их: продумывать сетап и бейзлайны, запускать обучающие прогоны, по замерам решать, что попадёт в финальную смесь * автоматизировать подготовку данных: выстраивать очистку, дедупликацию и валидацию так, чтобы любой новый датасет без ручной доводки приходил в готовый к обучению вид * добывать редкие и дефицитные домены: обучать классификаторы и кластеризаторы, которые вылавливают ценные сэмплы из сырых данных, и нарезать корпус на чистые датасеты по таксономиям * собирать данные разных форматов: генерация VQA, синтетические задачи, interleaved-данные — каждый формат устроен по-своему и требует своего подхода * обрабатывать миллиарды изображений: писать распределённый код, который прогоняет пайплайны на всём корпусе быстро и стабильно * находить слабые места в данных: разбираться, где модель проседает из-за корпуса — чего не хватает, что зашумлено или разбалансировано, — и исправлять это * развивать контур оценки: подключать свежие бенчмарки, следить за чистотой методики и не пускать тестовые данные в обучающий корпус Требования **Кто нам подходит:** Человек, который сможет провести данные от поиска источников до состава финальной смеси. Главное — умение ставить эксперименты и делать из них честные выводы. Опыт именно с VLM или LLM не обязателен: специфика осваивается быстрее, чем культура эксперимента **Что мы хотели бы видеть:** * хорошая база ML, твёрдое знание CV и NLP * понимание, как данные влияют на качество модели, и привычка при странностях в метриках первым делом смотреть в данные * уверенный Python и опыт обучения моделей на PyTorch * умение спланировать эксперимент и довести его до вывода, которому можно верить * самостоятельность и проактивность: берёте тему, разбираетесь, доводите до результата **Плюсом будут:** * опыт построения дата-пайплайнов и процессов контроля качества данных * опыт с распределённой обработкой (Spark, Dask, Airflow, YTsaurus) * опыт проведения ML-экспериментов на больших объёмах * публикации на профильных конференциях. Мы открыты к кандидатам разного уровня, и попадать во все пункты не обязательно. Если задачи откликаются — напишите нам, остальное обсудим. Условия **Что мы предлагаем:** * опыт претрейна из первых рук. Команд, обучающих VLM полным циклом, в стране единицы — вы пройдёте весь путь от сырых данных до готовой модели * вычислительные ресурсы под ваши эксперименты. Один из самых больших GPU-кластеров в России: проверка гипотезы о данных стоит обучающего прогона, и на такие прогоны вычислений у нас хватает * инфраструктура, которая уже работает. S3, YTsaurus, Airflow, DataLens, GitLab CI, wandb — всё для данных и экспериментов на месте, время уходит на исследования, а не на обвязку * задачи, на которые ещё нет ответа. Как собрать лучшие визуальные данные для претрейна, пока не знает почти никто в мире — разбираться предстоит в том числе вам * короткий путь от гипотезы до модели. Данные, которые вы отберёте, и гипотезы, которые подтвердятся, уходят в обучение следующей модели — а ей пользуются миллионы людей * комфортный современный офис рядом с м. Кутузовская * возможность выбрать удобный график – офис/гибрид/удаленка (в РФ) * годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * ипотека для сотрудников по дисконтной прогамме * бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров * вознаграждение за рекомендацию друзей в команду Сбера.
Location: San Francisco, CA Workplace: onsite Role Overview We’re hiring an onsite lead to run day-to-day execution for our robotics data collection pilot. You’ll guide a team of data collection operators, keep operations safe and consistent, and act as the main onsite point of contact for client stakeholders. Project Details Location: San Francisco, CA — 100% onsite Type: Full-time, short-term W-2 employee Schedule: Full-time; 8 hours/day, 5 days/week. 7:00 AM to 3:00 PM Duration: 6 weeks with possibility of extension Start: ASAP Compensation: $50/hour Work authorization: Must be authorized to work onsite in the U.S. Key responsibilities Ensure workforce and station readiness Own operator performance management, feedback, coaching, and corrective action Monitor adherence to SOPs, safety requirements, and agreed quality standards Triage operational issues and escalate technical faults to client teams Identify bottlenecks, drive process optimization and station utilization Track recurring issues, performance trends, and structured shift handovers Basic Qualifications Bachelor’s degree or equivalent work experience Hands-on experience leading robotic teleoperation and/or HRI data collection. Strong communication, coaching, and problem-solving skills in lab/field environments. Comfortable driving consistency, safety, and quality in repetitive workflows. Experience with gaming, simulation tools, or technical systems is a plus Strong hand-eye coordination and spatial awareness Comfortable using controllers, keyboards, or specialized interfaces for extended periods Basic computer skills, including PC and Linux troubleshooting. Working knowledge of MS Office and Google Drive Ability to follow detailed procedures with high accuracy Clear written and verbal communication skills Preferred Qualifications Exposure to robotics, autonomous systems, drones, or simulation environments Experience with teleoperation, remote control systems, or QA/testing workflows Familiarity with data collection, logging, or annotation processes Ability to quickly learn new software applications Interest in AI, robotics, or emerging technologies Experience working in structured, metrics-driven environments Please note that in order to verify work authorization as is required by Federal law (I-9 process), all new employees must complete a live video verification with their selected IDs and provide photos of these selected IDs within their first 3 days of employment. To know more details (Click here) In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire. In addition, we employ anti-fraud checks to ensure all candidates meet the requirements of the program. As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.
Location: Москва Наша цель — улучшать опыт клиента, предупреждая и предиктивно решая его проблемы и возникающие вопросы. Мы работаем с ключевыми продуктами банка и экосистемы Сбера (от дебетовых карт до СберПрайма) и стремимся сделать взаимодействие с банком и компаниями экосистемы простым, удобным и предсказуемым. Наш трайб активно разрабатывает AI-агентов на базе GigaChat для автоматизации клиентского обслуживания, а наша команда помогает с тестированием и оценкой качества внедряемых AI агентов. Обязанности * исследовать причины обращений клиентов: анализировать текстовые данные (NLP), выявлять триггеры и закономерности * строить и анализировать клиентские пути по различным продуктам и каналам, находить узкие места и возможности для улучшения * формировать и проверять гипотезы на основе данных из разных систем (транзакции, кликстрим, коммуникации, обращения) * участвовать в оценке качества работы AI-агентов и других сервисных сценариев, анализируя их влияние на клиентский опыт * готовить, запускать и оценивать A/B тесты в различных каналах: SMS, IVR, мобильное приложение * проводить углублённый анализ воронок, распределений, сегментов, чтобы находить инсайты для бизнеса и предлагать решения. Требования * уверенный SQL (сложные запросы, оконные функции, оптимизация) и опыт работы с базами данных * практическое знание Python для анализа данных (pandas, numpy, визуализация) * хорошая математическая подготовка, понимание статистики, опыт проведения A/B-тестов, работы с воронками, сегментацией * умение работать с большими объёмами данных, строить end-to-end анализ: от постановки задачи до выводов. будет плюсом: * опыт с PySpark/Hadoop * базовое понимание ML и NLP * опыт работы с LLM-платформами, опыт написания промптов Условия * комфортный современный офис рядом с м. Кутузовская * офисный формат работы * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * программа адаптации и помощь руководителя на старте * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера.
- Разработка, обучение и улучшение ML-моделей для решения NLP- задач; - Решение задач классификации и извлечения сущностей (NER);
Location: Ukraine; Spain; Serbia; Yerevan; Poland Workplace: remote Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide. Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits You will work in a senior pod alongside an FDE, an FDX, and Senior AI Engineers — contributing to real delivery work while building toward independent ownership. Requirements: Mindset Proactive and self-directed; you push for clarity rather than waiting for a ticket. Excellent communication and problem-solving skills. Comfortable with some ambiguity, with support from senior team members as you take on more. B2+ English, comfortable collaborating across distributed, multicultural teams. Technical depth Hands-on experience building or contributing to RAG systems, ideally in a production or near-production setting. Solid engineering fundamentals; Python and/or TypeScript proficiency. Productive in an unfamiliar codebase with some ramp-up support. Practical AWS experience (Lambda, S3, ECS, or similar); ready to grow into Bedrock and Bedrock AgentCore . Some experience with containers and CI/CD in real projects. Exposure to evaluating non-deterministic systems — you've contributed to or run test/eval cycles, even if you haven't owned a full eval suite end-to-end. Basic working knowledge of model/agent monitoring concepts. Awareness of cost and latency trade-offs when working with LLMs. Some hands-on exposure to the Claude ecosystem (Claude Code, CLAUDE.md, hooks, skills files) is a plus, or strong ability to ramp up quickly. Practical experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) in real projects. 2+ years of software or ML engineering experience, including some exposure to production systems. Solid AI/ML foundations — you understand what the models do well enough to reason about common failure modes. Nice to Have: Experience in one of the industries: financial services, insurance, healthcare. Consulting, professional services, or other embedded customer-facing delivery. AWS and Claude Code Certifications (or actively pursuing them). A2A: Interest in agent-to-agent interoperability concepts. CI/CD pipeline experience (GitHub Actions, GitLab CI). Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines. Experience in an additional language (Go, TypeScript, or Rust). Experience with Apache Spark, Apache Airflow, Kafkа. Experience with the Claude ecosystem — Claude Code, CLAUDE.md, hooks, skills files. Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build. MCP: you can say why an agent would prefer it to a REST integration, having authored a server is an additional plus. Responsibilities: Build and contribute to RAG system components under senior guidance, with growing autonomy. Write tests and help build out evaluation harnesses for the features you work on. Write production code across the stack (AI, backend services, data pipelines) with code review support. Help integrate AI components into backend services and RESTful APIs. Support deployment of systems to AWS (containerized, CI/CD), taking on more of this independently over time. Contribute to documentation, runbooks, and client handover materials. Participate in technical discussions and architectural decisions, with an eye toward taking on more of this independently. Support model evaluation efforts and help investigate and improve failure modes. Take on increasing ownership of components and technical decisions as you grow in the role. What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside FDE and FDX A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire: Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant HR Interview. Soft skills and expectations HM interview. Tech questions; a live engineering session is also possible
Location: San Francisco, CA Workplace: onsite Role Overview We’re hiring data collection operators to support physical AI programs. In this role, you’ll operate physical AI data collection systems (via teleoperation tools or guided interfaces) to generate high-quality real-world data used to train and evaluate AI models. This is hands-on, execution-focused work. You’ll be working with real hardware in structured environments, following defined scenarios, and helping produce the data that directly shapes how robots learn and perform. Project Details Location: San Francisco, CA — 100% onsite Type: Full-time, short-term W-2 employee Schedule: Full-time; 8 hours/day, 5 days/week. 7:00 AM to 3:00 PM Duration: 6 weeks with possibility of extension Start: ASAP Compensation: US$36/hour Work authorization: Must be authorized to work onsite in the U.S. Key responsibilities Operate robotic systems through VR or headset controls, robotic interfaces, and other teleoperation equipment Execute assigned data collection tasks to established procedures, maintaining consistency, accuracy, and data quality Troubleshoot basic hardware and connectivity issues Document issues and escalate technical failures to the appropriate teams Adapt to changes in workflows, equipment configurations, and procedures Comply with your safety, security, and operational requirements Basic Qualifications Bachelor’s degree or equivalent work experience Experience with gaming, simulation tools, or technical systems is a plus Strong hand-eye coordination and spatial awareness Comfortable using controllers, keyboards, or specialized interfaces for extended periods Basic computer skills, including PC and Linux troubleshooting. Working knowledge of MS Office and Google Drive Ability to follow detailed procedures with high accuracy Clear written and verbal communication skills Preferred Qualifications Exposure to robotics, autonomous systems, drones, or simulation environments Experience with teleoperation, remote control systems, or QA/testing workflows Familiarity with data collection, logging, or annotation processes Ability to quickly learn new software applications Interest in AI, robotics, or emerging technologies Experience working in structured, metrics-driven environments Please note that in order to verify work authorization as is required by Federal law (I-9 process), all new employees must complete a live video verification with their selected IDs and provide photos of these selected IDs within their first 3 days of employment. To know more details (Click here) In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire. In addition, we employ anti-fraud checks to ensure all candidates meet the requirements of the program. As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.
Location: Hybrid - Palo Alto or San Francisco 📍 Hybrid, Palo Alto or San Francisco (Hybrid – 2 days/week in office) Reports to: Director Data Science + Analytics Job Type: Full-time W2 About the Role We are looking for a pragmatic, hands-on Data Scientist to build and own the quantitative foundation for our clinical care delivery, patient treatment plan refinement, and retention engines. In our specialty care model, clinical health outcomes and business growth are directly linked: matching patients to their preferred, personalized treatment path leads to higher clinical efficacy, better satisfaction, and long-term retention. In this role, you won't just work with clean tabular data; you will bridge the gap between structured clinical metrics (lab values, symptom severity scores, dosage trajectories) and unstructured patient communications (visit transcripts, ambient scribe outputs, and intake survey dialogue). You will sit at the intersection of Data Science, Clinical Operations, and Product, serving as a core builder who transforms messy, multi-modal patient data into actionable clinical decision support and personalized care pathways. What You’ll Do Data Foundation & Pipeline Development Clean & Transform Multi-Modal Clinical Data: Build reliable, well-structured modeling tables and feature stores by parsing, cleaning, and joining raw datasets including lab results, symptom severity surveys, medication history, and raw visit transcripts. Establish Unstructured Data Workflows: Design robust data processing pipelines to convert unstructured clinical notes, orders and visit transcripts into structured, queryable relational tables. Transcript Mining & Feature Extraction Extract Patient Intent & Preference: Build lightweight NLP and LLM-based pipelines (using entity extraction, sentiment analysis, and topic modeling) to convert ambient visit transcripts into structured features. And provide insights into patient preferences in treatment pathway, communication, and modality, etc. Identify Friction Points: Process qualitative dialogue to automatically detect unaddressed obstacles or early side-effect reports before they lead to treatment discontinuation. Lookalike Cohorts & Patient Treatment Planning Lookalike Clustering Engine: Develop unsupervised segmentation models to cluster patients into "lookalike" cohorts based on baseline lab values, symptom profiles, and transcript-derived preferences. Outcome & Trajectory Forecasting: Build predictive models that estimate symptom reduction, time-to-relief, and potential side-effect risks across alternative treatment branches (e.g., immediate HRT vs. conservative step-therapy). Causal Inference & Retention Analytics Quasi-Experimentation on Care Protocols: Apply observational study methods (Propensity Score Matching, Difference-in-Differences, Survival Analysis) to evaluate non-randomized care pathways and quantify counterfactual patient outcomes. Drop-Off & Retention Optimization: Identify critical clinical touchpoints and dosage adjustment milestones that drive long-term program adherence, connecting clinical milestone achievement directly to patient retention and LTV. Research & Cross-Functional Collaboration Evidence Generation: Partner with the clinical research team to provide analytical support for peer-reviewed medical publications, white papers, and payer studies. Clinical Operations Alignment: Translate analytical findings, treatment protocol insights, and patient drop-off trends into actionable workflow improvements for clinical operations and care teams. What You Bring Technical Skills Programming & Querying: Advanced proficiency in SQL for data manipulation alongside strong Python skills for predictive modeling and data transformation. Machine Learning & Modeling: Practical experience applying clustering (segmentation), regression/classification, and survival analysis (e.g., scikit-learn, statsmodels, lifelines). NLP & Modern LLM Workflows: Hands-on experience with NLP techniques and LLM frameworks (e.g., transformers, Claude API, etc.) to parse, extract, and classify unstructured text data. Causal Inference Fundamentals: Solid working knowledge of quasi-experimental design, propensity score matching, and counterfactual reasoning on observational datasets. Analytical Capabilities Healthcare Data Intuition: Comfort working with messy, semi-structured, or missing healthcare datasets (lab results, Patient-Reported Outcome Measures/PROMs, EHR notes). Pragmatic "0-to-1" Builder Mindset: You enjoy doing the foundational data architecture work—cleaning JSON outputs, structuring features, and validating baseline models—before reaching for complex algorithms. Cross-Functional Communication: Ability to translate technical modeling outcomes into clear, intuitive insights for Clinical Operations and Product partners. Experience 2 to 4 years of hands-on data science or analytics experience delivering high-impact solutions. Experience working with healthcare, telehealth, digital health datasets. Demonstrated track record of parsing unstructured text/transcript data into structured modeling pipelines. Bachelor’s or Master’s degree in Biomedical Data Science, Health Informatics, Biostatistics, or a related quantitative field. Interview Process: Recruiter Screen- 30 mins Hiring Manager Screen- 30 mins Technical Screen- 1hr Panel Interviews- 3 hours + Lunch in Office in Palo Alto At this time, Midi is unable to provide visa sponsorship . Candidates must be authorized to work in the U.S. without current or future sponsorship needs. This is a full-time W2 position. The base salary range is 144K-172K and will depend on experience. Midi pays a competitive base salary, plus equity and benefits. While you’re waiting for us to review your portfolio, here’s some fun content to check out 🎥 https://www.youtube.com/watch?v=1px7i6MVjNg #LI-PS1 At this time, Midi is unable to provide visa sponsorship. All Candidates must be authorized to work in the United States without current or future sponsorship needs. Please note that all official communication from Midi Health will come from an @joinmidi.com email address. We will never ask for payment of any kind during the application or hiring process. If you receive any suspicious communication claiming to be from Midi Health, please report it immediately by emailing us at careers@joinmidi.com . Midi Health is an Equal Opportunity Employer. We are committed to pay equity and ensure that all qualified applicants receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status. Our compensation philosophy is based on fair, objective criteria and the impact of the role, regardless of an applicant’s salary history. Please find our CCPA Privacy Notice for California Candidates here .
- Build training datasets from real conversations and operational data. - Run fine-tuning jobs and compare tuned vs base models.
Проведение исследовательского анализа данных (EDA) для AI/ML-проектов. Разработка и валидация метрик оценки для ML-моделей (включая LLM).
• Мы ищем талантливого Data Scientist/ML Engineer в ML-команду отдела «Global и Локализация».
Ожидания от кандидата знание основ математической статистики и основных методов расчета A/B тестов, а также интерес к другим методикам (bootstrap, cuped, diff-in-diff и др.); глубокое понимание области NLP;
Location: Japan; China; Global; Canada; Hefei, China; Nagoya, Japan; Oosaka, Japan; Yokohama, Japan; Beijing, China; Shanghai, China; Changsha, Hunan Province, China; Dalian, China; Jinan, China; Tokyo, Japan; South Korea Workplace: remote As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. MAIN PURPOSE OF THE JOB We are looking for translators with experience in translating patents from English into Japanese (native-level fluency of Japanese) for a patent translation project. MAIN DUTIES Translate Biology, Chemistry patent documents from English into Japanese with original meaning conveyed in a manner that is readable and understandable to target audience. Additional Job Description Tool: XTM Volume per week: +5,000 words per week Start date: ASAP Requirements Have strong experience of Patent Translation such as Biology, Chemistry . Native level fluency of Japanese At least 3-years' experience in translating patent Good at using CAT Tools, such as, XTM and Trados etc. Prompt responses on emails If you are interested in this position, please send us your CV. Look forward to hearing from you.
Location: Santiago, Chile; Mexico Workplace: remote OVERVIEW Are you tech-savvy? Have a passion for quality? We are looking for Data Raters to work on projects aimed at advancing AI technologies. Join us for a unique chance to kickstart your career in the AI field! This project is an excellent starting point for entry-level candidates. We offer comprehensive learning support, making it a great opportunity to gain experience in data annotation and data rating within the AI field—an industry currently in high demand for skilled specialists, especially those with expertise in localization and linguistic proficiency. MAIN DUTIES - Follow project-specific guidelines to conduct research on e-commerce data. - Evaluate the usefulness of product filters and results based on the research. - Rate the e-commerce data according to the guidelines provided. Project Details Start Date: Immediately after completing the qualification process Duration: Ongoing Schedule: This is a freelance opportunity; the workload is based on project needs. Weekly hours may vary. Employment Type: Freelance/Independent Contract Location: Remote Language: Spanish Pay Rate: $6/hour - Based on tasks completed By applying, you'll become part of our Freelance community, opening doors to a range of projects tailored to your skills and availability, particularly highlighting localization and linguistic expertise. Payment rates for future projects may vary, ensuring fair compensation that reflects your location, industry, and skill set. Joining us means contributing to our current project and becoming part of our dynamic network. This is a unique chance to enhance global user experiences and apply your language skills in meaningful ways. Requirements Fully Proficient in Spanish Linguistic competency in English equal to the following: ILR Level 5 or CEF C2 Must be located in Chile/ Mexico Web-savvy and able to work in a fast-paced environment Preferably previous experience in Search Relevance tasks, experience with e-commerce searches/websites Excellent online research skills Attention to detail Performing enough research during the allocated time, working within short throughputs Reliable computer system and internet connection Ability to follow instructions in English and comply with the project conventions and rules expected by the client Must sign a Non-Disclosure Agreement to protect client confidentiality Must pass training and a required quality test before starting work When you join Welocalize, you have the opportunity to bring your career to the next level: ... receive steady volume of work and long-term partnership {where this applies} ... professional development: work on exciting projects that will empower you keep learning and growing ... work with multicultural, international team with a great variety of documents and content types ... 24-hour 6-day a week support from our Community team. If this opportunity sounds appealing to you, apply below. As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com
Location: Chile; Argentina; Brazil; Turkey Workplace: remote OVERVIEW Are you tech-savvy? Have a passion for quality? We are looking for Data Raters to work on projects aimed at advancing AI technologies. Join us for a unique chance to kickstart your career in the AI field! This project is an excellent starting point for entry-level candidates. We offer comprehensive learning support, making it a great opportunity to gain experience in data annotation and data rating within the AI field—an industry currently in high demand for skilled specialists, especially those with expertise in localization and linguistic proficiency. MAIN DUTIES - Follow project-specific guidelines to conduct research on e-commerce data. - Evaluate the usefulness of product filters and results based on the research. - Rate the e-commerce data according to the guidelines provided. Project Details Start Date: Immediately after completing the qualification process Duration: Ongoing Schedule: 20 hours per week This is a freelance opportunity; the workload is based on project needs. Weekly hours may vary. Employment Type: Freelance/Independent Contract Location: Remote Language: German Pay Rate: $7/hour - Based on tasks completed By applying, you'll become part of our Freelance community, opening doors to a range of projects tailored to your skills and availability, particularly highlighting localization and linguistic expertise. Payment rates for future projects may vary, ensuring fair compensation that reflects your location, industry, and skill set. Joining us means contributing to our current project and becoming part of our dynamic network. This is a unique chance to enhance global user experiences and apply your language skills in meaningful ways. Requirements Fully Proficient in German Linguistic competency in English equal to the following: ILR Level 5 or CEF C2 Must be located in Chile/ Brazil/ Argentina/ Turkey Web-savvy and able to work in a fast-paced environment Preferably previous experience in Search Relevance tasks, experience with e-commerce searches/websites Excellent online research skills Attention to detail Performing enough research during the allocated time, working within short throughputs Reliable computer system and internet connection Ability to follow instructions in English and comply with the project conventions and rules expected by the client Must sign a Non-Disclosure Agreement to protect client confidentiality Must pass training and a required quality test before starting work When you join Welocalize, you have the opportunity to bring your career to the next level: ... receive steady volume of work and long-term partnership {where this applies} ... professional development: work on exciting projects that will empower you keep learning and growing ... work with multicultural, international team with a great variety of documents and content types ... 24-hour 6-day a week support from our Community team. If this opportunity sounds appealing to you, apply below. As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com
Location: Suriname; India; Philippines; Nigeria Workplace: remote OVERVIEW Are you tech-savvy? Have a passion for quality? We are looking for Data Raters to work on projects aimed at advancing AI technologies. Join us for a unique chance to kickstart your career in the AI field! This project is an excellent starting point for entry-level candidates. We offer comprehensive learning support, making it a great opportunity to gain experience in data annotation and data rating within the AI field—an industry currently in high demand for skilled specialists, especially those with expertise in localization and linguistic proficiency. MAIN DUTIES: *Follow guidelines to check the quality of filters and options in desktop and mobile views. *Check if filters and options help customers make decisions or suggest good alternative products. *Ensure filters and options match what customers are looking for based on their queries. *Determine if the filters and options are relevant and reflect the customer’s preferences. *Review your assessments for accuracy and consistency Project Details Start Date: Immediately after completing the qualification process. Duration: Ongoing Schedule: 5 -15 hours weekly; set your own schedule. This is a freelance opportunity; the workload is based on project needs. Weekly hours may vary. Employment Type: Freelance/Independent Contract Location: Remote Language: Dutch Pay Rate: $2.25/hour - Based on tasks completed By applying, you'll become part of our Freelance community, opening doors to a range of projects tailored to your skills and availability, particularly highlighting localization and linguistic expertise. Payment rates for future projects may vary, ensuring fair compensation that reflects your location, industry, and skill set. Joining us means contributing to our current project and becoming part of our dynamic network. This is a unique chance to enhance global user experiences and apply your language skills in meaningful ways. Requirements Fully Proficient in Dutch Proficient in English Web-savvy and able to work in a fast-paced environment Preferably, prior experience or familiarity with Relevance tasks and expertise in e-commerce searches/websites. Excellent online research skills Attention to detail Ability to conduct thorough research within specified time constraints and effectively managing short throughputs. Reliable computer system and internet connection Must sign a Non-Disclosure Agreement to protect client confidentiality Completion of a language assessment, learning module, and a mandatory quality test is required prior to starting work. When you join Welocalize, you have the opportunity to bring your career to the next level: ... receive steady volume of work and long-term partnership {where this applies} ... professional development: work on exciting projects that will empower you keep learning and growing ... work with multicultural, international team with a great variety of documents and content types ... 24-hour 6-day a week support from our Community team. If this opportunity sounds appealing to you, apply below. As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com
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