This is a product focused data science position sitting within a dedicated Agentic AI team. The core responsibility is co-owning the development and direction of an internal Agentic AI framework: ensuring it scales to a growing list of use cases and delivers a strong developer experience for data scientists building on top of it. This is not a pure research role. It combines hands on engineering product thinking and close collaboration with AI Engineers to build something that other data scientists rely on daily.
What the Work Looks Like Day to Day
Partner with product teams and business leaders to understand and define Agentic AI use cases
Collaborate with data scientists across global teams to gather feedback on the agent building experience and translate it into framework improvements
Shape and drive the evolution roadmap for the Agentic AI framework
Apply GenAI and Agentic AI techniques to solve real business problems
Build and maintain resilient production grade algorithmic and agentic pipelines
Write clean well structured code following engineering best practices
Deepen applied knowledge across machine learning optimization statistical modeling and GenAI
Technical Stack
Cloud:Microsoft Azure Google Cloud Platform Kubernetes
Languages:Python Spark (preferred); SQL for analytical work
Big data ecosystem:Databricks BigQuery Spark
Dev tools:GitHub Jira Confluence (Agile DevOps environment)
BI tools:PowerBI or Tableau (basic familiarity useful)
What Is Required
Masters degree in a quantitative field (Statistics Operations Research Computer Science Applied Mathematics Systems Engineering Economics) OR a Bachelors or Engineering degree with strong consecutive data science experience
At least 2 years of delivering production grade data science or algorithmically enabled applications with at least some of that experience involving GenAI based solutions
Solid Python skills; Spark experience is a plus
Experience with or genuine interest in building tools and frameworks used by other data scientists
Strong analytical thinking across optimization simulation predictive modeling and experimentation
Comfortable taking ownership navigating ambiguity and working across distributed global teams
What Strengthens an Application
Prior experience building developer tooling internal platforms or frameworks for data science teams is a genuine differentiator here. This role sits at the intersection of engineering and product and candidates who have thought about developer experience not just model performance will stand out.
Working Model and Location
This role is based in Warsaw Poland on a hybrid working arrangement. Regular on site presence in Warsaw is required. Full remote is not available for this position.
The RoleThis is a product focused data science position sitting within a dedicated Agentic AI team. The core responsibility is co-owning the development and direction of an internal Agentic AI framework: ensuring it scales to a growing list of use cases and delivers a strong developer experience for...
The Role
This is a product focused data science position sitting within a dedicated Agentic AI team. The core responsibility is co-owning the development and direction of an internal Agentic AI framework: ensuring it scales to a growing list of use cases and delivers a strong developer experience for data scientists building on top of it. This is not a pure research role. It combines hands on engineering product thinking and close collaboration with AI Engineers to build something that other data scientists rely on daily.
What the Work Looks Like Day to Day
Partner with product teams and business leaders to understand and define Agentic AI use cases
Collaborate with data scientists across global teams to gather feedback on the agent building experience and translate it into framework improvements
Shape and drive the evolution roadmap for the Agentic AI framework
Apply GenAI and Agentic AI techniques to solve real business problems
Build and maintain resilient production grade algorithmic and agentic pipelines
Write clean well structured code following engineering best practices
Deepen applied knowledge across machine learning optimization statistical modeling and GenAI
Technical Stack
Cloud:Microsoft Azure Google Cloud Platform Kubernetes
Languages:Python Spark (preferred); SQL for analytical work
Big data ecosystem:Databricks BigQuery Spark
Dev tools:GitHub Jira Confluence (Agile DevOps environment)
BI tools:PowerBI or Tableau (basic familiarity useful)
What Is Required
Masters degree in a quantitative field (Statistics Operations Research Computer Science Applied Mathematics Systems Engineering Economics) OR a Bachelors or Engineering degree with strong consecutive data science experience
At least 2 years of delivering production grade data science or algorithmically enabled applications with at least some of that experience involving GenAI based solutions
Solid Python skills; Spark experience is a plus
Experience with or genuine interest in building tools and frameworks used by other data scientists
Strong analytical thinking across optimization simulation predictive modeling and experimentation
Comfortable taking ownership navigating ambiguity and working across distributed global teams
What Strengthens an Application
Prior experience building developer tooling internal platforms or frameworks for data science teams is a genuine differentiator here. This role sits at the intersection of engineering and product and candidates who have thought about developer experience not just model performance will stand out.
Working Model and Location
This role is based in Warsaw Poland on a hybrid working arrangement. Regular on site presence in Warsaw is required. Full remote is not available for this position.