Вакансии

Проект Raft AI4BI — платформа, объединяющая BI, DWH и AI-аналитику, позволяющая пользователям задавать вопросы к данным на естественном языке и получать аналитику и визуализации. Продукт используется крупными заказчиками в ритейле, финансах, производстве и других отраслях. Кого ищем Специалиста, который самостоятельно доводит внедрение AI4BI у клиента от подписанного контракта до реальной эксплуатации, работая руками, а не через постановку задач большой команде. В проектной группе с ним работают разработчик и DevOps, а архитектор подключается при необходимости новых решений. Аналитика в команде нет, обследование, модель данных, ТЗ, витрины и приёмка — зона ответственности руководителя проекта. Разработчик реализует, DevOps отвечает за контур и деплой. Вторая часть роли — развитие аккаунта, выявление новых потребностей клиента и формулирование следующих этапов работ. Задачи: — Обследовать ландшафт заказчика: источники, качество данных, доступы, интеграционный контур — Проектировать аналитическое решение: ER-модели, зерно и структура витрин, семантический слой — Писать ТЗ и спецификации интеграций — Проектировать пайплайны загрузки: REST/SOAP API, ETL/ELT, потоковая доставка через Kafka/RabbitMQ — Вести проект: скоуп, сроки, риски, статусы, коммуникация с заказчиком от аналитика до директора — Собирать и проверять данные самостоятельно с помощью SQL и Python — Проводить демо, UAT, обучение пользователей, передавать проект в поддержку — Формулировать и обосновывать задачи для архитектора при необходимости новых решений — Вести карту аккаунта и инициировать расширения: новые домены, интеграции, тираж на смежные подразделения Требования: Обязательно: — Уверенный уровень SQL: оконные функции, CTE, чтение планов запросов, оптимизация — Опыт ведения проектов внедрения от старта до сдачи с небольшой командой (2–4 человека), включая системный анализ и постановку задач — Системный анализ с фокусом на моделирование данных: нормализованные и звёздные модели, SCD, выбор зерна витрины, ER-диаграммы — Опыт проектирования аналитических решений и интеграций: REST/SOAP API, ETL/ELT, загрузка из нескольких гетерогенных источников — Python для работы с данными: pandas, requests, разбор ответов API, трансформации, проверка качества выгрузки — Использование AI-инструментов для быстрого создания PoC/прототипов (Claude Code, Cursor, Codex) — Понимание брокеров сообщений (Kafka/RabbitMQ): когда нужны, описание контрактов событий Плюсом: — Знание Apache Superset: датасеты, семантический слой, дашборды, разграничение доступа — Знание доменов закупок и/или продаж — Опыт скрапинга данных — Понимание процессов CI/CD Отбор: — Интервью с рекрутером — Тестовая задача с навайбкодиванием — Техническое интервью: обсуждение тестового задания, SQL, работа с данными, моделирование и системный анализ — Финальное интервью: управление проектами, коммуникация с заказчиками и командой Условия: — Работа с реальными внедрениями AI/BI-решений и крупными заказчиками — Возможность влиять на проект целиком — от обследования и проектирования до внедрения и развития клиента — Команда технических специалистов и возможность роста в AI и работе с данными — Полный рабочий день с гибким графиком — Заработная плата до 200 000 рублей gross

Задачи: — сопровождение и развитие аналитической отчетности с фокусом на работу с данными, SQL-логикой и корректностью бизнес-показателей; — автоматизированный отчет, который обращается к данным витрины с использованием PySpark, обработка данных на Python и Pandas, формирование итоговой HTML-страницы; — анализ и доработка источников данных; — контроль корректности показателей, актуальности бизнес-логики, качества данных и стабильности формирования отчета; — доработка SQL-логики, обработки данных, структуры отчета и итоговой HTML-страницы. Дополнительно: — участие в развитии AI-агента по отчетности, автоматизирующего text2sql-задачи: перевод пользовательских запросов в SQL, сбор данных, проверка показателей, подготовка структурированных ответов для руководства банка; — понимание SQL, аналитического контекста, структуры витрин данных; — проверка корректности сгенерированных запросов и результатов; — участие в настройке логики взаимодействия агента с данными. Требования: — опыт работы в разработке на Python от 3 лет; — уверенное владение Python, Pandas, SQL, PySpark (Hadoop/Spark); — знание matplotlib/seaborn, Jupyter Notebook; — знание HTML; — навыки работы с Git, умение читать код DS и приводить его к инженерным стандартам production. Условия: — график работы 5/2, офисный формат (м. Кутузовская); — оформление по ТК РФ, оплачиваемые больничные листы; — спортивные и корпоративные мероприятия; — программа обучения; — добровольное медицинское страхование; — и многое другое.

Группа Компаний “Вита Плюс” — фармацевтический холдинг, основанный в 2005 году, представленный на региональном рынке под брендами: «Вита Плюс», «Аптека нашего города», «Семейная аптека», «Склад Лекарств», «Вавилон Фарм», «Первая аптека». Компания объединяет более 3000 профессионалов и достигает ежегодного роста и развития. Задачи: — Выявление аномалий и глубокая сегментация данных для поиска неочевидных корреляций — Бенчмаркинг и сравнение показателей сети с рынком для выявления слепых зон — Сценарное моделирование развития событий с построением нескольких вариантов прогноза — Стресс-тестирование влияния внешних факторов на маржинальность — Разработка имитационных моделей для оценки влияния изменений параметров на прибыль — Декомпозиция целей, определение ключевых метрик и создание индексных показателей — Трансформация данных в стратегические планы и подготовка материалов для ТОП-менеджмента Требования: — Продвинутый SQL (оконные функции, CTE) — Python (Pandas, NumPy, SciPy) или R для статистического моделирования — Понимание регрессии, корреляции, кластеризации, теории вероятностей — Знание разницы между Gross Profit, Net Profit, EBITDA, ROI, ROMI — Системное мышление: видеть цепочку X → Y → через 3 месяца Z — Коммерческая интуиция: опыт в ритейле, e-com или дистрибуции — Здоровый скептицизм к данным: не верить «средней температуре по больнице», искать хвосты распределения Условия: — Зарплата от 100 000 ₽ (обсуждается по итогам собеседования) — Официальное оформление по ТК РФ — График 5/2 — Удаленный формат работы или гибрид — Современный стек, приветствуется инициатива и новые инструменты — Возможность влиять на процессы с первых месяцев, отсутствие жесткой бюрократии

Location: New York City, New York What you’ll be part of Garner is on a mission to transform the U.S. healthcare system — and we’re the only proven player doing exactly that. We partner with employers to redesign how healthcare works: applying 550+ proprietary clinical metrics across 80+ specialties to a dataset of 320M+ patients to identify the best-performing doctors, then using compelling incentives to steer members to the care that helps them get healthier, faster. The result is a rare “win win” — better care and lower costs for both members and employers. In just five years, our work has helped over 2.5 million people access higher-quality care and saved $1B in healthcare costs. We recently raised our Series E and have doubled five years running. If you've ever wanted your work to solve a problem that touches every person in this country, this is the opportunity to do exactly that. You'd be joining a team fundamentally reimagining healthcare in the U.S. — and using AI to scale that impact further and faster than anyone else can. Who we want This is a role for someone who wants to work on a hard problem, deliver real impact and be pushed to be the best version of themselves. As an Associate Applied Scientist, you’ll be embedded in the Applied Science team. Our members rely on us to answer hard questions — Which doctor should I see? What will it cost? When should we reach out, and how? — and the quality of those answers is determined by the algorithms behind them. This is not a dashboards or descriptive-analytics role. You will own production systems end-to-end: framing the problem, defining the objective function, choosing the right approach (ML, optimization, heuristics, expert systems, or a hybrid), shipping it, and improving it against real-world outcomes. The closest analog outside healthcare is a quantitative researcher at a top hedge fund. What you will do Ship production algorithmic systems end-to-end, from problem framing to launch to iteration Frame messy, real-world healthcare and business constraints into clear objectives, tradeoffs, and decision frameworks Define the set of metrics needed to judge whether a solution is working, and validate solutions before they ship Choose the right approach for each problem, from machine learning to optimization to heuristics to simple rules, based on what the problem actually calls for Bring new ideas to your work, experimenting with approaches beyond the obvious to get better results Produce rigorous, well-validated work others can rely on, and review your peers' code and analyses Build a deep understanding of the healthcare economy and Garner's place in it To make the role concrete, here are two problems on our near-term roadmap: Provider tiering optimization. Build a tiering algorithm that jointly optimizes geographic access and total-cost-of-care savings across our doctor network. The objective function, constraints, and tradeoff surface are all open design questions. Member engagement model. Build an ML system that ingests claims data and in-app behavior to choose the right channel and moment for each touchpoint — SMS, push, phone, or email — to influence member behavior toward better-quality, lower-cost care. What we're looking for A Bachelor's or Master's degree (in progress) in Computer Science, Mathematics, Statistics, Economics, or a related STEM field, with an expected graduation date of Fall 2026 or Spring 2027. A bias toward action, quickly translating ideas into working prototypes to test approaches. Strong applied problem-solving skills, with the ability to define good metrics and then deliver solutions that improve them. A solid command of the methods your work calls for and the data your models depend on. Strong judgment in choosing between statistical models, heuristics, optimization approaches, and simpler algorithmic methods depending on the problem. Strong communication skills, with the ability to present your work clearly to senior stakeholders. A desire to do work that matters: and to be held to a high standard while doing it. You're energized by a mission with measurable outcomes, not just good intentions. You engage with AI tools as part of how you do your best work, and hold yourself accountable to outcomes that matter beyond your team’s metrics. What you’ll get here You’ll work on problems that matter, at a company working to change healthcare at scale. You’ll work at the intersection of AI and systemic healthcare reform, where the problems we solve are as interesting and compelling as the mission. At Garner, you’ll take on real, ambitious problems with real ownership and autonomy, alongside exceptional, principles-based people who genuinely want you to win. It’s demanding by design. You’ll be challenged to stretch beyond what you thought possible and receive consistent coaching to help you grow and do the best work of your career. This isn't the right fit for everyone, and that's intentional. The people here are driven by what's at stake for real people, and that's what gives our intensity its purpose. Technologies we use Python, SQL, AWS, Snowflake, pandas, XGBoost, PyTorch, HuggingFace, modern LLM tooling and eval frameworks. We pick tools based on the problem, not the resume — bring your judgment. Please note: we are unable to sponsor or take over sponsorship of an employment visa at this time. Compensation The target base comp range for this role is $150,000. Individual compensation will depend on qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive plan and benefits package, including: flexible PTO, Medical/Dental/Vision plan options, 401(k) with company match, flexible spending accounts, Teladoc Health, and more. Few roles offer this combination: work that is genuinely hard, a mission that is genuinely important, and a team that is genuinely invested in your success. If that’s what you’re looking for, we’d love to meet you. Fraud and Security Notice: Please be aware of recent job scam attempts. Our recruiters use getgarner.com and garnerhealth.com email domains exclusively. If you have been contacted by someone claiming to be a Garner recruiter or a hiring manager from a different domain about a potential job, please report it to law enforcement here and to candidateprotection@garnerhealth.com . Equal Employment Opportunity: Garner Health is proud to be an Equal Employment Opportunity employer and values diversity in the workplace. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. Garner Health is committed to providing accommodations for qualified individuals with disabilities in our recruiting process. If you need assistance or an accommodation due to a disability, you may contact us at talent@garnerhealth.com .

Требуется специалист с хорошим знанием Python (Pandas, Numpy, MatPlotLib и другие аналитические библиотеки), отличным знанием SQL (Postgre с умением написания оконных функций), опытом построения отчетности (PowerBI предпочтительно), уверенным знанием Excel (ВПР, Сводные таблицы и пр.). Опыт работы в антифрод-аналитике или риск-менеджменте является преимуществом. Понимание алгоритмов ML также является плюсом. Задачи: — разрабатывать и выгружать обязательную отчетность для Центрального Банка РФ; — подготавливать аналитические отчеты и дашборды для смежных подразделений компании; — участвовать в модернизации и настройке систем мониторинга транзакций (антифрод-систем).

Задачи: — Разрабатывать новые отчеты и поддерживать существующие; — Автоматизировать подготовку и доставку отчетов с помощью Python; — Проектировать концепты дата-моделей и витрин для своих отчетов; — Участвовать в проверке данных для витрин в продакшене; — Плотно взаимодействовать с разными командами: CRM, антифрод, маркетинг, финансы, випы и т.д.; — Поддерживать актуальность и прозрачность показателей, документировать метрики и логику расчетов; — Участвовать в разработке различных бизнес-моделей; — Создавать и дорабатывать дашборды в Tableau; — Искать возможности для автоматизации и улучшения существующих решений. Требования: — Уверенное владение основными конструкциями Python и понимание принципов работы языка; — Практический опыт использования функций, генераторов, декораторов и т.д.; понимание принципов организации кода: модули, пакеты, зависимости; — Умение писать надежный код с обработкой исключений и логированием; — Опыт работы с Pandas; — Опыт работы с Git; — SQL: умение читать большие сложные витрины, дебажить их и грамотно писать запросы; — Понимание принципов оптимизации запросов и работы с большими объемами данных; — Tableau или любой другой BI тул: базовый уровень. Будет плюсом: — Опыт работы с Airflow. Условия: — Удалённая работа из любой точки мира с возможностью посещения офиса в Москве; — Достойный уровень заработной платы; — Сильная техническая команда и обмен опытом; — Сложные задачи и использование новых технологий; — Отсутствие бюрократии и технологическая свобода; — Возможность карьерного роста и профессионального развития; — Открытая и свободная атмосфера; — 50% компенсация оплаты изучения английского языка; — Частичная оплата занятий спортом.

Задачи: — участие в создании и поддержке аналитических решений для повышения эффективности маркетинговых кампаний; — применение методов машинного обучения, особенно uplift-моделирования, для оптимизации взаимодействия с клиентами и повышения ROI; — построение uplift-моделей по сегментам для разных групп; — разработка uplift-моделей для различных номиналов промоакций с последующей оптимизацией; — прогнозирование RFM; — участие в проведении A/B тестов, расчет финансовых эффектов от внедрения моделей, генерация признаков для моделей. Требования: — базовое понимание статистики и теории вероятностей; — опыт работы с Python (Pandas, NumPy); — знание основ машинного обучения (линейная регрессия, деревья решений, случайный лес); — понимание концепции uplift-моделирования; — опыт работы с табличными данными; — понимание принципов распределенных вычислений (PySpark); — опыт коммерческой разработки. Технологии и инструменты: — работа с данными: pyspark, SQL, S3; — классический ML и uplift: Scikit-learn, XGBoost, LightGBM, CatBoost, scikit-uplift; — разработка и версионирование: Jupyter Notebook, VS Code/PyCharm, git; — ML инфраструктура: JupyterHub, MLFlow, Airflow, PostgreSQL; — ML: Transformers, SGLang, Triton; — процессы: Jira, Confluence.

Задачи: — Разработка и внедрение автономных ИИ-агентов и генеративных моделей (LLM, мультимодальные системы) для ускорения проектирования, разработки и развертывания ERP-систем, а также создания интеллектуальных интерфейсов автоматизации — от генерации кода до обработки естественно-языковых запросов пользователей. — Создание ИИ-сервисов и автономных агентов для автоматизации бизнес-процессов. — Обучение и тонкая настройка LLM (Large Language Models) и других ML-моделей под задачи компании. — Анализ данных, разработка алгоритмов для прогнозирования, оптимизации и принятия решений. — Интеграция ИИ-решений в существующие продукты компании. — Участие в научно-исследовательских проектах, публикация результатов (при желании). Требования: — Опыт в работы в IT от 5-ти лет. — Опыт работы в области Machine Learning, Deep Learning или Data Science от 3-ех лет. — Знание Python и ряда библиотек для ML/DL таких как TensorFlow, Pandas, PyTorch, scikit-learn и др. — Опыт работы с NLP, LLM (GPT, Llama, Mistral и т. д.), RAG, автономными агентами. — Понимание принципов работы ERP-систем (желательно). — Умение работать с большими данными (SQL, NoSQL). — Знание методов обучения с подкреплением (RL) — будет плюсом. — Английский язык (уровень для чтения технической документации). Условия: — Официальное оформление и стабильный доход по ТК РФ. — Все льготы и преимущества работы в аккредитованной ИТ-компании. — Программа ДМС с первых дней. — Работа в офисе с гибким началом рабочего дня. — Московский офис в шаговой доступности от м. Динамо, оборудованный всем необходимым для комфортной работы и отдыха.

Задачи: — Выстроить продуктовую аналитику: события, воронки, ключевые метрики. — Считать и визуализировать метрики по данным продукта (SQL, PostgreSQL). — Анализировать поведение пользователей в вебе, iOS и Android. — Формулировать и проверять продуктовые гипотезы, готовить выводы для команды. — Помогать в описании требований к новым фичам вместе с продуктом и разработкой. Требования: — Опыт работы продуктовым аналитиком от 1 года. — Уверенный SQL. — Понимание продуктовых метрик (retention, конверсии, воронки, когорты). — Знание статистики: проверка гипотез, значимость, доверительные интервалы. — Опыт проведения A/B-тестов: дизайн, расчёт выборки, интерпретация результатов. — Опыт построения дашбордов и отчётов. Будет плюсом: — Python (pandas) для анализа данных. — Опыт в медтехе или health-продуктах.

О позиции Разработка дашбордов и аналитики на Apache Superset с элементами AI для поддержки экспертизы лекарственных средств и медицинских изделий. Обязанности • Разработка и поддержка интерактивных дашбордов в Apache Superset • Написание и оптимизация сложных SQL-запросов, создание витрин данных • Кастомизация дашбордов (Jinja, CSS, Python) • Внедрение AI/ML-решений для аналитики и прогнозирования • Взаимодействие с заказчиками, сбор требований, презентация результатов Требования • Высшее техническое / ИТ-образование • Опыт BI-разработчика от 2 лет • Опыт работы с Apache Superset от 1 года • Продвинутый SQL • Опыт работы с PostgreSQL / ClickHouse / MS SQL • Знание Python (Pandas, SQLAlchemy) • Понимание DWH и моделирования данных Будет плюсом: опыт AI/ML в аналитике, Power BI/Tableau, Airflow, работа в фарме или госсекторе. Условия • Зарплата от 500 000 тенге • Работа в офисе в Астане • Социальный пакет по ТК РК • Участие в проектах цифровизации государственной экспертизы

Задачи: — Анализ бизнес- и операционных данных — SQL-запросы и работа с PostgreSQL, MongoDB — Подготовка отчётности и дашбордов в Power BI — Расчёт KPI, ad-hoc аналитика, поиск закономерностей и аномалий — Обработка и автоматизация данных с помощью Python Требования: — Опыт Data Analyst от 2 лет — Уверенный SQL — Практический опыт с PostgreSQL и MongoDB — Python (pandas), Power BI — Аналитическое мышление и понимание бизнес-метрик — MongoDB Aggregation Pipeline будет плюсом Условия: — Собственные IT-продукты в логистике и e-commerce — Реальные возможности карьерного и профессионального роста. — Корпоративные мероприятия, льготная программа Invictus GO и динамичная корпоративная культура.

Location: Almaty, Kazakhstan Workplace: OnSite WHY WORK AT HIGGSFIELD AI? Higgsfield AI is the fastest-scaling generative AI company in history, hitting $1B in annual revenue run rate, 25M+ users worldwide, 6M+ generations per day, and powering 390 of Fortune 500 brands. We're building at the absolute frontier of AI-powered video creation and next-generation creative tools. Joining Higgsfield means becoming part of a high-impact team shaping the future of AI-native experiences, at a company that isn't just moving fast, but rewriting what fast looks like. WHAT THIS ROLE MEANS AT HIGGSFIELD This role owns how Higgsfield measures its product - from the first sign-up to whether people come back. You are the measurement owner for onboarding, first generation, the paywall, plans and credits, and retention. Product managers ship fast here - your job is to make sure they ship knowing. You make sure: - Every product decision has a number attached to it before it ships and after it ships - Experiments are designed to be readable, and then read honestly - including when the answer is “this didn’t work” - The events the product emits can be trusted; you own the definition, not just the query - A PM gets an answer in hours, not next sprint You are the person who decides what “it worked” means. WHAT YOU WILL DO Product measurement - Own the core product metrics: activation, first-generation success, generation depth, free→paid conversion, repeat usage, retention by cohort and segment. - Define each metric once, write the definition down, and hold the line on it - one definition across dashboards, decks, and Slack. - Instrument new features before launch, with product and engineering: which events, which properties, what success looks like, when we call it. - Watch the health of the event stream itself - tracking drift, double counting, missing parameters, naming breakage and find the problem before a decision gets made on top of it. Experimentation - Design A/B tests properly: hypothesis, one primary metric, unit of randomization, MDE, sample size, run length, guardrail metrics. - Read them honestly: significance, peeking, novelty effects, sample-ratio mismatch, segment heterogeneity. - Separate “we proved this works,” “we proved this doesn’t,” and “we can’t tell from this test” - and say which one out loud. Product & monetization analysis - In-product funnel work: onboarding and quiz, first generation, paywall, checkout, plan choice, credit top-ups. - Pricing and packaging analysis: plan mix, credit consumption, unit economics per generation, margin by feature and by model. - Feature adoption and its real effect on retention and revenue — separating “users who do X retain better” from “making people do X improves retention.” - Behavioural segmentation: casual creators vs corporate/B2B, new vs returning, by model and by use case. Mixing them hides everything that matters. Making it usable - Build the few dashboards PMs actually open on their own — decision-shaped, not comprehensive. - Write short readouts a non-analyst can act on. Visualize data for humans, not for other analysts. - Automate recurring reporting so your hours go to new questions, not refreshes. - Work in SQL, Python, BigQuery and product analytics tools. We use AI heavily - resourcefulness beats syntax. WHO WE'RE LOOKING FOR We're looking for an analyst with opinions. You should have: - Strong SQL: window functions, cohorts, funnels and retention on raw event data, without help. - Python at working level for analysis (pandas, notebooks). Entry level is fine - we use AI heavily. - Real experimentation experience: you have designed tests, run them, and killed features with the results. - Statistical honesty: you know what a p-value does and does not entitle you to say, and you have refused to call a flat test a win. - Understanding of subscription + one-time purchase mechanics: recurring vs one-off revenue, refunds, plan changes, deferred value of unspent credits. - The instinct to check the instrument before explaining the movement - a surprising number is a claim, not a fact. - Ownership: you decide what's worth analyzing, you chase the fix, you follow the recommendation to a shipped change. - Clear written and spoken English, B2+. Backgrounds that often do well: - Product analysts from consumer subscription or PLG products - Growth/BI analysts who moved into product and stayed - Early-startup analysts who built product measurement from zero - Data scientists who got tired of models and want decisions WHAT THIS ROLE IS NOT This role is not a fit if you: - Wait for a ticket to tell you what to analyze - Want to build models more than you want to change decisions - Need a data engineering team and clean tables to exist before you can start - Would report a lift you don't believe in because a stakeholder wants it - Need perfect data before you can say anything useful - Want predictable 9–5 workdays HIRING PROCESS - Screening call (30 min) - Hiring-manager screen (30 min) - Business case (1 hour) - Take-home with real-shaped data (7 days, ~10–12 hours of work) - Team interview (60 min) - Paid on-site trial (1 month) WHAT WE OFFER - Competitive base salary in USD, based on your experience, skills, and the scope of the role. - Equity participation through the company’s stock option program, giving you the opportunity to share in Higgsfield’s long-term growth. - Relocation support to Almaty for candidates moving from another city or country. - A highly collaborative, fast-paced environment where you can work directly with experienced leaders and have a meaningful impact on the product and company. - Opportunities for professional growth, ownership, and career development as the company scales. - Company-provided equipment, meals, transportation, or other office benefits.

Location: Remote We're hiring a Junior Trader to join our trading team. You'll work directly with senior traders across strategies on centralized and decentralized venues, and take on your own responsibilities quickly. We don't require prior DeFi experience. We do require that you're quantitative, technical, and able to move fast without breaking things. WHAT YOU'LL DO - Execute and manage trades across centralized (CEX) and decentralized (DEX) venues — order books, AMM pools, and concentrated liquidity positions. - Monitor positions, inventory, and P&L in real time. Identify risks early and act on them. - Build and improve the tooling the desk runs on: position trackers, reporting dashboards, hedging workflows, reconciliation. - Analyze market and execution data to answer questions that matter — where slippage comes from, which pools are actually profitable, how our fill quality compares to the market. - Develop real depth in market structure and protocol mechanics (AMMs, PMMs, lending protocols) and bring it back to the desk. WHAT WE'RE LOOKING FOR - 0–3 years of experience — recent graduates with strong technical credentials, or candidates from quant research, engineering, data, or markets-adjacent roles looking to move onto a trading desk. - Strong quantitative foundation: probability, statistics, and the instinct to reach for data before opinions. - Python preferred, ideally applied to financial modeling or data analysis (pandas, notebooks, working with messy datasets). Adjacent tooling — R, MATLAB, SQL, serious Excel modeling — counts. - Real interest in crypto and DeFi. Professional crypto experience isn't required; demonstrated engagement with the space is. - Sound judgment under pressure. Markets move at 3am and things break. We need someone who stays composed, thinks clearly, and escalates early. - Precise communicator - Self-directed and adaptable; comfortable operating with autonomy across time zones in a remote-first environment. NICE TO HAVE - Personal trading, market-making, or on-chain activity of any kind — a portfolio, a bot, an arbitrage script, a Dune dashboard. - Familiarity with Solana tooling (Jupiter, Orca, Drift) or EVM DeFi (Uniswap, Aave, Curve). - Exposure to algorithmic or systematic trading. - Machine learning or large-scale data analysis (regression, tree-based methods, classification). - Internships or prior work at a trading firm, market maker, exchange, or protocol. WHAT YOU'LL GET - Direct mentorship from traders running real capital — you'll learn by working alongside them, not from a curriculum. - Responsibility as fast as you can earn it, with clear feedback on where you stand. - Exposure across the full stack of a trading operation: execution, risk, tooling, counterparty relationships, and market structure. - A front-row seat as equities, commodities, and crypto converge on-chain.

Задачи: - Работа с различными по сложности структурами данных и их источниками - Поддержка существующей кодовой базы — отладка, ускорение работы - Разработка новых программных решений для бизнеса (B2B-продукты) Требования: - Коммерческий опыт разработки ~1 год - Хорошее знание Python, его инфраструктуры и встроенных библиотек - Знание как минимум одного популярного веб-фреймворка - Знание как минимум одного популярного фреймворка для обработки данных (numpy / pandas / polars) - Знакомство с методами оптимизации кода (векторизация, распараллеливание, async) - Хорошее знание реляционных СУБД, опыт написания автотестов - Docker, Linux, Git Условия: - Оформление по ТК РФ - ДМС после испытательного срока - Формат работы: удалённо или гибрид (офис — башня «Империя», Москва-Сити)

Requirements 2+ years with Python including strong knowledge of data libraries (pandas, multiprocess, Google Cloud SDK) 2+ years of experience in ETL/ELT technologies (REST API, GraphQL, DBT, etc. ) and data pipeline orchestration (e.g., Airflow, Astronomer, DBT cloud, etc) Hands-on experience with Snowflake Problem-solving and root cause analysis in live production systems along with experience querying and transforming large volumes of data, data quality and data validation Experience in SQL (SQL Server, Oracle, MySQL, BigQuery, Snowflake) Comfortable working with serialized data format (JSON, AVRO, XML, CSV) as well as compressed and encoded files Comfortable with ingesting data using REST APIs, data transformations and data loading/unloading techniques English proficiency sufficient to work in an international environment Nice to have Capable of designing and implementing data pipelines over cloud architecture Experience working with CI/CD deployments Experience working with GIT We offer Projects for such clients as PayPal, Wargaming, Xerox, Philips, Adidas and Toyota; Competitive compensation that depends on your qualification and skills Career development system with clear skill qualifications Flexible working hours aligned to your schedule Options to work remotely Corporate medical insurance covering services of private and public medical centers English courses online Corporate parties and events for employees and their children Internal conferences, workshops and meetups for learning and experience sharing Gym membership compensation 5 days of paid sick leave per year with no obligation to submit a sick-leave certificate Any questions? Anna hh@itransition.com

Location: Limassol, Cyprus Workplace: hybrid Mayflower is a technology company building highload products used by millions of people worldwide. Operating at the scale of one of the world's top-50 websites, we solve complex engineering challenges and create solutions that power real-time entertainment for a global audience. Now we look for a Data Scientist to join our ML team Job Responsibilities Machine Learning & Modeling • Develop and train machine learning models for prediction, classification. • Build and evaluate regression, classification, clustering, and time-series models. • Design feature engineering pipelines and data preprocessing workflows. • Evaluate model performance, robustness, and production readiness. • Deploy and maintain ML models in collaboration with ml-ops teams. Data Analysis & Exploration • Explore large datasets to identify patterns, trends, and hidden relationships. • Perform statistical analysis and hypothesis testing. • Distillate open-source datasets by proprietary data via LLM agents • Detect anomalies, outliers, and unexpected metric movements. • Translate business or product questions into analytical tasks. Data Pipelines & Infrastructure • Work with data pipelines and streaming data systems. • Process and transform large datasets using Python and SQL. • Work with event streams and messaging systems (Kafka). • Contribute to data quality monitoring and dataset validation. • Work with analytical databases and data warehouses. Model Monitoring & Experimentation • Design experiments and evaluate model performance in real environments. • Implement monitoring for model performance and data drift. • Support A/B testing and experimentation frameworks. • Improve models based on production feedback and metrics. Cross‑Functional Collaboration • Work closely with ML engineers, data engineers, and product teams. • Communicate model results and analytical insights clearly. • Contribute to the development of ML best practices within the team. You’ll thrive here if you have • Strong Python programming skills for data science and machine learning. • Experience working in Jupyter / Python notebooks for experimentation and analysis. • Strong experience with pandas and numerical data processing . • Experience with SQL databases and complex analytical queries. • Experience working with ClickHouse or other analytical columnar databases. • Experience working with Kafka or other streaming data platforms . • Experience building and evaluating machine learning models using libraries such as scikit‑learn, XGBoost, LightGBM, or similar . • Understanding of statistics, probability, and experimental design . • Experience working with large datasets and data preprocessing pipelines. Nice to Have • Experience with deep learning frameworks (PyTorch or TensorFlow). • Experience deploying ML models to production environments. • Experience working with Computer Vision models (OpenCV, CNNs, object detection frameworks). • Experience with distributed data processing or large-scale ML systems. • Familiarity with ML monitoring, experiment tracking, and model versioning tools. Conditions We know that great talent deserves great conditions, so here's what you can expect when joining us: EU-based employment contract and a 3-year Cyprus work visa with full support for your relocation and visa processes, including assistance for your family. Full relocation package: flights to Limassol for you and your family, a company-covered apartment for the first month, and full relocation support to make your move smooth and hassle-free. Transparent performance reviews twice a year, with bonus opportunities and salary adjustments. Private medical insurance for you and your family, a corporate mobile plan (unlimited in Cyprus with roaming included), and interest-free support for car purchases. Provident fund (Cypus): a long-term savings plan co-funded by you and the Company together (available after probation) that grows throughout your time with us in Cyprus. Mindfulness & well-being support, including psychological assistance with 50% coverage. 50% coverage of school and kindergarten fees for your children. Fully covered sports benefits, and also access to in-house electric scooters and bike rentals, and cycling purchase compensation. Investment in your growth: paid language courses and access to suited-for-you development programs, including conferences, training programs, and coaching to support your professional journey. A culture of recognition: a peer reward program to celebrate your contributions. A fully equipped office in Limassol’s city center, with everything you need for deep work and collaboration. Free catering in the office and an in-house coffee bar with high-quality drinks and a health bar stocked with nutritious snacks. A strong engineering culture: international teams, corporate events, team buildings, and hackathons—because great work happens in great communities. Recruitment process HR interview (40 min); Technical interview (1.5 hour); Final interview (60 min).

Location: London Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. You will work within a data function responsible for making complex financial datasets accessible and reliable for research and trading. You will collaborate directly with Quantitative Researchers and Traders to understand data requirements, onboard new sources and build datasets that support systematic strategies and discretionary trading decisions. Your future role within QRT Collaborate with Quantitative Researchers and Traders to design datasets that support systematic strategies and discretionary trading decisions Extract, clean and aggregate data from a wide range of raw sources and formats using QRT’s data framework Manage the full process of onboarding new datasets, from initial assessment through to production Investigate and resolve data issues to reduce the time required to make new datasets available to users Develop robust data extraction processes with a strong focus on correctness and data quality Explore and implement new approaches to data extraction that improve the tools available for onboarding complex datasets Your present skillset 3+ years of experience in Data Engineering or a similar role working with financial data Advanced Python development skills, including experience with libraries such as Pandas, Polars and NumPy Strong focus on correctness, with the ability to critically assess code and data quality regardless of source Experience working with SQL and relational databases Experience working with both traditional and alternative financial datasets Demonstrated interest in financial markets and the application of data to investment research and trading Experience within quantitative finance is beneficial Excellent communication skills with the ability to collaborate with Quantitative Researchers, Traders, Engineers, management and external data providers Ability to operate effectively in a high performance environment with rapid delivery cycles QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Location: New York, NY About Us: EvolutionIQ’s mission is to improve the lives of injured and disabled workers and enable them to return to the workforce, saving billions of dollars in avoidable costs and lost productivity to the US and global economies and make insurance more affordable for everyone. We are currently experiencing massive growth and to accomplish our goals, we are hiring world-class talent who want to help build and scale internally, and transform the insurance space. Our team is our #1 priority, and we have been named one of Inc.’s Best Workplaces 3 years in a row! About You : As a Staff Data Scientist on the Data Science & Insights team, you will serve as the analytics expert for your internal stakeholders, using data & models to help them make better decisions. You thrive in dealing with ambiguous decision-making problems, small & big data modeling and insight generation, both for clients and internal stakeholders. You’ll explore and analyze new datasets as we enter new markets and quickly make critical recommendations for your fellow team-mates in Engineering and Product Management. You love diving deep into hard analytical questions, striving in answering ambiguous open ended questions with clear data-driven insights and recommendations. You’re supercharged by having interesting, unsolved problems continually present themselves and inform both the technical as well as business side of the business for critical decisions.  You demonstrate ownership and leadership to build out the analytical muscle at EvolutionIQ and demonstrate value by clearly shaping the path of new developments and high ROI initiatives. Your Impact: You will work closely with Engineering & Product to improve our team and clients understanding of claims data; you work closely with business stakeholders to leverage internal data that demonstrates product ROI and give them mission-critical insights to steer the company in new high ROI directions. The ideal candidate will ensure EIQ tells excellent stories through data & modeling that clearly and accurately communicate the impact and ROI of our products internally and externally. Additionally, you will partner with product managers to do rapid iterations on new product ideas, scope the business opportunity of new product features, and measure ROI of ongoing user engagement with a variety of products. What You'll Achieve (Performance Outcomes) : Support the decision-making of EvolutionIQ’s leadership team in critical recommendations such as which product features we should build as they lead to highest projected ROI or measuring impact of existing product through sophisticated experimental design setups that best leverage the user feedback we have on challenging small data, high variance outcome problems. Uncover new product research directions (hypothesis generation) through exploratory data analysis and hypothesis testing. Create data insights to win clients by helping define and build the sales & marketing narrative Present results to internal stakeholders as well as our clients in the insurance industry Generate meta-analysis across clients to drive product & sales strategies Build, own, and standardize client-facing analysis and reporting on existing products across multiple clients and ROI dimensions Work closely with the ML team to analyze the impact of modeling results, debug data issues, and communicate findings to colleagues and clients. Write efficient and reliable relational database queries, create re-usable dashboards, write design documents, write clean & maintainable code for reproducible analytics via CLI tools, perform code reviews, and maintain state-of-the-art engineering practices. Continue to grow and learn in the data & analytics space, focusing on business problems that require making sense of large-scale structured and unstructured datasets. Oversee the integration of cross-organizational projects, drive improvements and recommendations for your engineering and product counterparts, and define operational goals and objectives. Provide direction and accomplish results for business leaders through solving hard measurement problems that impact business bottom line About You (Key Competencies): 7+ years of data analysis/quantitative experience, preferably within Machine Learning and Product environments At least 2 years experience in mentoring or tech-leading junior analysts and business-critical analytics projects Masters degree in statistics or equivalent quantitative field with strong focus on applied, data-driven solutions. Sophisticated knowledge of statistics, linear & non-parametric modeling, and advanced SQL engineering experience. Designed, implemented, and analyzed A/B or multi-arm experiments with clear recommendations for product direction & development. Proficient in the use of Python, pandas, Jupyter notebooks, and SQL-based analytics dashboards (e.g., Google’s DataStudio / Looker or Tableau), and familiarity with standard statistical packages and visualization tools in Python. Skilled data illustrator who makes market-ready graphs, slides, figures, and presentations Excellent communication, storytelling, and presentation skills Proven understanding of Product and Business analytics, fundamentals, and processes Proven ability to synthesize data insights into actionable recommendations Proven ability to handle large datasets via SQL and/or map-reduce analytics and data aggregation as needed. Even Better if You Have: PhD in statistics or related quantitative field with strong focus on applied, data-driven solutions. Experience in Bayesian statistics and causal inference methods Written production quality code for reproducible analytics pipelines Work-life, Culture & Perks: Compensation: The base salary range is up to $250K, with flexibility depending on a candidate’s background and experience. An annual bonus plan and company equity plan (RSUs) are also included in our compensation package. Well-Being: Medical, dental, vision, short & long-term disability, life insurance and AD&D, and 401k matching. Additional family, wellness, and pet benefits. Home & Family: Paid time off and sick leave, 100% paid parental leave (16 weeks for primary caregivers and 12 weeks for secondary caregivers). We offer a flexible schedule for new parents returning to work. Office Life: Catered lunches, happy hours, pet-friendly spaces, and monthly technology stipend. Growth & Training: $1,000/year for each employee for professional development, as well opportunities for tuition reimbursement. Sponsorship: We are open to sponsoring candidates currently in the U.S. who need to transfer their active visa. Please check with our Recruiting team if your visa is applicable for transfer. EvolutionIQ appreciates your interest in our company as a place of employment. EvolutionIQ is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.