Вакансии

Сейчас мы ищем Senior IT-специалистов с коммерческим опытом от 5 лет для работы на международных аутстафф-проектах.

-Проверка гипотез и поиске новых точек роста продукта (бизнес линии). -Определение ключевых драйверов роста в продукте.

Location: Moldova Company Background Coherent Solutions is a global digital product engineering company founded in 1995 and headquartered in Minneapolis, Minnesota. With a presence in nine countries and a team of more than 1,700 engineers, the company provides custom software development and engineering services across web and mobile applications, cloud, DevOps, and data. Coherent Solutions works with clients worldwide to build and scale digital products while fostering a culture of collaboration, transparency, and continuous professional growth. Project Description You will work with senior engineers on internal classical machine learning initiatives. The role combines structured learning, practical delivery, and gradual ownership of increasingly complex tasks. Technologies Python, pandas, NumPy, scikit-learn, Jupyter SQL XGBoost, LightGBM MLflow FastAPI Git, Docker, pytest What You'll Do Prepare and validate structured datasets for machine learning tasks, including cleaning, transformation, encoding, scaling, and missing-value handling; Conduct exploratory data analysis to identify patterns, data quality issues, and opportunities for modeling; Build, test, and compare ML models for tasks such as regression, classification, clustering, dimensionality reduction, and anomaly detection; Develop and select features with guidance from senior engineers; Run experiments, tune model parameters, and evaluate results using appropriate validation approaches and metrics; Help maintain reproducible ML pipelines, notebooks, experiment tracking, and technical documentation; Write and maintain automated tests for data and model-related code; Support the delivery of models through REST APIs or batch-processing workflows; Document model assumptions, results, limitations, and technical decisions; Work closely with senior engineers, incorporate feedback, and gradually take ownership of more complex tasks; Job Requirements 1+ year of hands-on Python development experience, including experience with pandas, NumPy, scikit-learn, and Jupyter; A strong foundation in statistics, probability, and linear algebra, plus exploratory data analysis skills; An understanding of supervised and unsupervised learning, and practical experience with regression, classification, clustering, dimensionality reduction, and anomaly detection; Experience preparing structured datasets, including cleaning, transformation, encoding, scaling, and missing-value handling, plus practical feature engineering and feature-selection skills; An understanding of train/validation/test splits, cross-validation, data leakage, overfitting, and regularization; the ability to select appropriate evaluation metrics, compare models, and perform error analysis; Familiarity with hyperparameter tuning and reproducible ML pipelines; SQL skills for data extraction and analysis; The ability to expose models through REST APIs or batch-processing workflows; Familiarity with Git, automated testing, Docker, and basic model monitoring; The ability to explain model behavior, assumptions, limitations, and results; English at B2 level or higher; Nice To Have XGBoost, time-series analysis, recommendation systems, MLflow, model interpretability, cloud services, production ML monitoring, and GenAI, LLM, RAG, prompt-engineering, or agent-development experience; What Do We Offer The global benefits package includes: Technical and non-technical training for professional and personal growth; Internal conferences and meetups to learn from industry experts; Support and mentorship from an experienced employee to help you professional grow and development; Health insurance; Sports activities to promote a healthy lifestyle; Flexible work options, including remote and hybrid opportunities; Referral program for bringing in new talent; Work anniversary program and additional vacation days.

Ищем инженера с практическим опытом работы с геопространственными данными, дорожными графами и/или алгоритмами маршрутизации. - Разработка и оптимизация алгоритмов маршрутизации и построения маршрутов (VRP, TSP, роутинг с ограничениями по времени / весу / зонам);

Чем предстоит заниматься: составлять стратегические и тактические планы по развитию проекта; контролировать стоимость сроки и качество работ;

Опыт проектирования высоконагруженных распределённых систем: горизонтальное масштабирование, отказоустойчивость, балансировка нагрузки, кэширование, очереди, rate limiting, graceful degradation. Опыт встраивания ML-сервисов в корпоративную архитектуру: интеграция с API Gateway, IAM/SSO, корпоративными шинами, системами мониторинга и журналирования.

Location: Москва Оптимизируем наши модели под форматы популярных инференсных фреймворков. Задача создание инфраструктуры для эффективного инференса наших моделях во всех популярных фреймворках: Diffusers, FastVideo, SGLang, vLLM, Comfy-UI. А также создание воркеров для доступа к инференсу наших моделей на fal.ai, Arena.ai и др. Обязанности * Разработка и оптимизация high-load пайплайнов распределенного инференса (PyTorch) с использованием FSDP, Tensor/Sequence Parallelism. * Имплементация моделей в популярных фреймворках: Diffusers, SGLang, vLLM, FastVideo, Comfy-UI, Transformers * Развертывание воркеров для инференса моделей Требования * Экспертный уровень Python, PyTorch, torch.distributed. * Опыт масштабного инференса моделей с FSDP/TP/PP. * Понимание работы разных типов данных (bf16, fp8). * Опыт работы с SGLang, vLLM, Transformers * Понимание принципов работы диффузионных моделей * Английский язык B2+ Условия * комфортный современный офис рядом с м. Кутузовская * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * система обучения для профессионального и карьерного развития * расширенный полис ДМС с первого дня работы и страхование для семьи * льготная программа ипотеки для сотрудников * бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров * вознаграждение за рекомендацию друзей в команду Сбера.

- Strong analytics and data visualization experience; - 7+ years of SQL;

Задачи: — Анализировать и повышать эффективность закупки рекламного трафика из in-app, social и web-источников: оценивать источники, каналы, кампании, аудитории и связки по ключевым закупочным метрикам, определяя зоны для масштабирования и оптимизации. — Проводить когортный и сегментный анализ, ad hoc-анализ закупки трафика. — Системно находить точки роста, формулировать, приоритизировать и тестировать growth-гипотезы на основе данных: от оптимизации закупки трафика, креативов и рекламных платформ до улучшения монетизации, удержания и окупаемости пользователей. — Анализировать и улучшать эффективность алгоритмов автоматизации закупки трафика: оценивать качество решений, искать причины просадок, формулировать требования к доработкам и адаптировать логику под новые источники, рекламные платформы и бизнес-цели. — Проводить предиктивную и инициативную аналитику, помогая заранее выявлять риски, просадки эффективности и новые возможности для роста. — Строить и поддерживать аналитические и функциональные dashboards. — Проверять точность ключевых отчетов, данных, трекинга и аналитических систем; работать с данными из рекламных платформ, BI, CRM, MMP, attribution tools и внутренних баз. — Координировать аналитические задачи в рамках своего направления: взаимодействовать с analytics team, следить за качеством аналитики и помогать переводить результаты анализа в бизнес-рекомендации. — Анализировать и улучшать продуктовые метрики собственных приложений, находя точки роста в удержании, монетизации, пользовательском поведении и общей эффективности продукта. Требования: — Опыт работы в data analytics от 7 лет. — Опыт в mobile app analytics и рекламной медиации для приложений с рекламной монетизацией: понимание работы mediation-платформ, ad networks, waterfall / bidding-логики, eCPM, fill rate, ARPDAU, impressions, ad revenue и влияния рекламной монетизации на продуктовые метрики. — 4+ года опыта с digital marketing, performance marketing, paid acquisition или growth marketing. — Глубокая экспертиза в ключевых закупочных и продуктовых метриках и их практическом применении: LTV, ROAS, ROI, CPA, CPC, CPM, CPI, CTR, CR, retention, ARPU и др. — Опыт проведения когортного анализа, ad hoc-анализа, оценки экспериментов и проверки гипотез. — Умение находить неочевидные инсайты в данных и превращать их в конкретные бизнес-рекомендации. — Опыт работы с MMP, attribution и tracking tools: Adjust, Voluum, Amplituda, MixPanel, Firebase или аналогичными платформами. — Опыт работы с SQL для проведения ad hoc-анализа, извлечения данных и моделирования. — Знание Python или R для аналитики, автоматизации и моделирования. — Понимание принципов маркетинговой атрибуции, tracking, conversion measurement и качества данных. — Навыки работы и построения отчетностей, dashboards в BI-инструментах (Looker). — Опыт работы с BigQuery и другими инструментами современного data stack: GitLab, Docker, Google Cloud (Container Registry, Workflows, Cloud Run). — Опыт работы с большими объемами данных и способность самостоятельно выстраивать аналитическую логику. — Сильные аналитические способности и системное мышление. — Внимание к деталям, высокий уровень самоорганизации и ответственность за результат. — Умение понятно доносить технические выводы до нетехнических команд. — Высшее образование в области математики, прикладной математики, статистики, data science, информационных технологий или смежных дисциплин. Условия: — Удаленный формат взаимодействия. — График: с 10:00 до 19:00 по времени Кипра. — 20 дней отпуска и оплачиваемые больничные. — Зарплата - по договоренности, в зависимости от Вашего уровня и опыта. — Работаем по праздничному календарю Кипра. — Испытательный срок - 3 месяца.

-Исследовать большие объемы данных о покупательском поведении и находить закономерности для решения бизнес-задач. -Разрабатывать и улучшать ML-модели для прогнозирования оттока и отклика пользователей.

- Тестирование web-приложений на всех уровнях: UI, API, интеграции; - Разработка и поддержка автоматизированных тестов на Playwright + JavaScript, + Java/python;

Location: Dublin, Ireland; London, England Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What’s the opportunity? The Research, Analytics & Data Science (RAD) team at Intercom uses data and insights to drive evidence-based decision-making. We're a team of data scientists and product researchers who use data - both big and small - to unlock actionable insights about our customers, our products and our business. We generate insights that build customer empathy, drive product strategy and shape products that deliver real value to our customers. We’re now seeing strong demand for data scientists who can apply their expertise directly with our most strategic customers. As a Forward Deployed Data Scientist, you’ll embed with customers to build Enterprise-grade Fin deployments. You’ll play a pivotal role in transforming how our most strategic customers scale customer support — working closely with them and our go-to-market teams to design, build, and implement data-driven solutions that unlock measurable impact. You’ll also feed insights from these frontline deployments back into Intercom’s product and strategy — helping shape the future of AI customer service. This is a high-ownership role for someone who thrives in ambiguous environments, is energized by solving complex, real-world problems with data, and is motivated by seeing their work translate into both customer impact and product evolution. What will I be doing? Drive the adoption of Fin by helping customers automate and scale their support operations. Embed with strategic customers to understand their support workflows, data, and business challenges — to identify and implement opportunities where AI can deliver measurable impact. Steer customers toward best practices in measurement and AI adoption to realize the full value of Fin. Partner closely with Sales, Success, and Product to deliver seamless customer experiences and successful deployments, and to create feedback loops that shape product development. Use AI to prototype, test, and scale data-driven solutions, building tools that make us faster and more effective in driving Fin adoption and customer impact. What skills do I need? Proven ability to apply data science in real-world business contexts to drive measurable outcomes. Strong collaboration mindset; skilled at working across Sales, Success, Product, and Engineering. High adaptability and ownership: able to shift between deep technical analysis and high-level strategic framing. Excellent communication skills, both technical and non-technical. Rapid prototyping with systems thinking: you know when a customer needs a fast, bespoke answer, and when to build something others will keep using. Excellent SQL and production-aware Python, you write code other people can run, not just code that runs once and are experienced applying analytical and statistical methods to real business problems. Experience with AI/ML evaluation, LLM-driven applications, or conversational AI. Willing to travel and work on-site with customers to build deep relationships and uncover insights firsthand. Bonus skills and attributes Experience in technical consulting, customer-facing analytics, or SaaS product data science. Experience reframing the problem, not just solving it, you've spotted when the question you were handed wasn't the right one, and changed what got worked on. Experience applying AI to scale the data science workflow. Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world. In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. At Fin, we want to give people what they need to do the best work of their careers. Our benefits and programs are designed to support your health and wellbeing, your family, your time away from work, and your financial future. Offerings vary by location in line with local practices and requirements. Learn more about working at Fin and the benefits we offer at fin.ai/careers . Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records. Policies Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week. We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values . Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

— Define service-level objectives for production services. — Build and maintain useful reliability dashboards.

● Сопровождение серверов и СУБД PostgreSQL. ● Написание и поддержка скриптов Shell, Python, Ansible.

Анализировать эффективность маркетинговых активностей и искать точки роста; Разрабатывать и поддерживать систему аналитической отчетности;

– Разработка, создание и оптимизация масштабируемых ETL-процессов и конвейеров обработки данных. – Разработка и поддержка решений в области бизнес-аналитики, хранилищ данных и аналитических наборов данных.

– Администрирование корпоративных серверов: Linux и Windows, настройка и устранение неполадок. – Настройка сети, устранение неполадок.

Создавать систему эффективного хранения больших данных и доступа к ним для ML-разработчиков. • Майнинг данных.