Senior Data Scientist

The ideal candidate will be responsible for maintaining product and industry knowledge. You will work in a team-oriented environment that accelerates operational efficiency.

Responsibilities

• Develop and implement advanced machine learning models and algorithms to solve complex business problems.
• Design and optimize scalable data pipelines and machine learning workflows on cloud platforms.
• Collaborate with cross-functional teams to understand business requirements and deliver data-driven solutions.
• Participate in exploring new methodologies and techniques in data science.
• Communicate findings and insights to stakeholders in a clear and actionable manner.
• Contribute to the development of data governance policies and best practices.
• Perform data analysis, reviewing and optimizing algorithms, ensuring adherence to best practices, and collaborating with the Data Science team to identify and address analysis issues.
• Maintain the data infrastructure, participating in architectural discussions, and ensuring that the infrastructure aligns with the overall design, scalability, and security goals.

Qualifications

• 5+ years in a quantitative role (data science, product analytics, or experimentation) in high-growth or fintech environments
• 5+ years of experience in applied data science, with deep hands-on exposure to forecasting, predictive modeling, or marketplace systems.
• Fluency in with a track record building time series modelings and forecasting
• Experience building product metrics from scratch and operationalizing them for decision-making
• Excellent communication skills with PMs, engineers, risk/finance partners, and executives
• Strategic instincts beyond significance tests—clear thinking about tradeoffs (conversion vs. risk vs. cost vs. user experience)
• Advanced degree (MS or PhD) in a quantitative field (e.g., Statistics, Computer Science, Economics, Operations Research).
• Expertise in time-series forecasting techniques and practical understanding of model trade-offs across performance, explainability, and scalability.
• Proficiency in Python, SQL, and tools such as scikit-learn, PyTorch/TensorFlow, and forecasting libraries.
• Demonstrated experience with model monitoring, debugging, and long-term maintenance in production environments.
• Strong communication and storytelling skills - able to simplify complexity and influence executive stakeholders.
• Self-directed, intellectually curious, and comfortable leading ambiguous projects from 0→1.

What we offer:

• Opportunity to work on cutting-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, vision, dental, etc.
• Corporate social events
• Professional development opportunities
• Well-equipped office

About Us:

Grid Dynamics (Nasdaq: GDYN) is a digital-native technology services provider that accelerates growth and bolsters competitive advantage for Fortune 1000 companies. Grid Dynamics provides digital transformation consulting and implementation services in omnichannel customer experience, big data analytics, search, artificial intelligence, cloud migration, and application modernization. Grid Dynamics achieves high speed-to-market, quality, and efficiency by using technology accelerators, an agile delivery culture, and its pool of global engineering talent. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the US, UK, Netherlands, Mexico, and Central and Eastern Europe.

To learn more about Grid Dynamics, please visit www.griddynamics.com. Follow us on Facebook, Twitter, and LinkedIn.