We are looking for a Lead Data Scientist who can transform data into actionable solutions and impactful machine learning products.

You will be responsible for guiding the full data science process, from framing problems and exploring data to building models, running experiments, and delivering clear insights. Collaboration with product and engineering teams will be key to achieving meaningful business results.

 

Responsibilities

• Translate strategic goals into clear data science challenges with defined metrics for success
• Explore, preprocess, and combine complex data sources, engineering features that enhance model performance
• Build, test, and optimize models for prediction, classification, ranking, natural language processing, and time-series analysis
• Plan and analyze experiments, including A/B and multi-arm trials, and conduct causal studies for reliable conclusions
• Communicate results through engaging narratives, visualizations, and actionable guidance
• Partner with product and engineering to launch models in production and monitor their effectiveness

 

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field
• Minimum of 5 years’ experience applying data science in production settings or similar environments
• At least one year of experience leading and managing technical teams
• Strong foundation in statistics, probability, and experimental design
• Advanced proficiency in SQL and at least one general-purpose programming language, with hands-on experience in machine learning libraries and frameworks
• Experience working with large-scale datasets and distributed data processing technologies
• Deep understanding of model assessment, validation, and monitoring using both offline and online metrics
• Expertise in data visualization and the ability to communicate findings to executive stakeholders
• Familiarity with MLOps principles and collaboration with data or platform engineering teams
• Fluent English skills, both written and spoken, at B2+ level or higher

 

Nice to have

• Experience in areas such as natural language processing, forecasting, recommendation engines, or anomaly detection
• Knowledge of causal inference and advanced experimentation methods
• Hands-on experience with feature stores, streaming data, or online machine learning systems
• Familiarity with cloud data platforms and modern data warehousing solutions
• Experience mentoring colleagues and working on cross-functional initiatives

 

We offer

• International projects with top brands
• Work with global teams of highly skilled, diverse peers
• Healthcare benefits
• Employee financial programs
• Paid time off and sick leave
• Upskilling, reskilling and certification courses
• Unlimited access to the LinkedIn Learning library and 22,000+ courses
• Global career opportunities
• Volunteer and community involvement opportunities
• EPAM Employee Groups
• Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn