Staff Data Scientist

Staff Data Scientist at Grid Dynamics is a hands-on role centered on delivering a complex, production-grade machine learning solution. You’ll combine traditional data science with emerging foundation model approaches, while building for MLOps reliability and improving how the team delivers, tests, and maintains ML systems. The role is based in the United States (onsite) and emphasizes close partnership with the client’s core engineering team to keep system stability and performance strong.

What you’ll work on

• Build and productionize machine learning solutions that cover both classical approaches and emerging foundation model methods for time-series forecasting
• Contribute to MLOps excellence by proposing, designing, and optimizing ML system architecture
• Refactor and improve Azure DevOps (ADO) and Azure Data Factory (ADF) pipelines for scalability and reliability
• Strengthen end-to-end delivery through improved solution architecture, code quality, and maintainability
• Collaborate with engineering and business stakeholders to maintain alignment, clarity of requirements, and effective solution delivery

Responsibilities

• Collaborate cross-functionally with engineering and business teams to ensure alignment, clarity of requirements, and effective delivery of solutions
• Drive MLOps excellence by proposing, designing, and optimizing system architecture, including refactoring ADO and ADF pipelines for scalability and reliability
• Enhance SDLC practices by improving overall solution architecture, code quality, and maintainability across the development lifecycle
• Establish and promote best practices by defining and implementing effective ways of working within the project team
• Partner closely with the client’s core team to ensure rapid identification and resolution of bugs, maintaining system stability and performance

Requirements

• Azure Cloud expertise, including Azure DevOps, Azure Databricks, and Azure Data Factory
• Strong programming skills in Python and PySpark, with experience in multiprocessing and multithreading for scalable data processing
• Deep expertise in machine learning, including classical time-series models, gradient boosting/tree-based methods, deep learning, and emerging foundation models for time-series forecasting
• Demonstrated strengths in decision-making and ownership, with a proactive, results-oriented mindset
• Proven ability in knowledge sharing, collaboration, and initiative, contributing to team growth and project success
• Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field

Benefits

• Opportunity to work on cutting-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package, including medical insurance, vision, dental, etc.
• Corporate social events
• Professional development opportunities
• Well-equipped office
• Onboarding must occur in person and you may be asked to travel to attend

Nice to have

• Experience with AWS cloud services, including designing and deploying scalable data and ML solutions
• Hands-on experience with Databricks Asset Bundles (DAB) for managing, packaging, and deploying Databricks projects across environments