Top Data Science Jobs in Warsaw

Lead strategic workforce planning initiatives by partnering with business leaders and cross-functional teams to diagnose needs, define recommendations, and enable data-driven workforce strategies. Support SWP product enablement, training, and scaling (30%+ capacity) and advise on skills, AI/tech impacts, location strategies, and external workforce optimization. Drive stakeholder engagement, change management, and strategy execution across a global, matrixed HR environment.

Lead end-to-end delivery of multiple software projects by creating and managing plans, running agile ceremonies, tracking KPIs, coordinating distributed teams and stakeholders, mitigating risks, and ensuring on-time delivery using project management tools (Linear).

As a Senior Product Manager, you will define product vision, analyze market trends, manage product KPIs, and collaborate with teams to deliver innovative solutions.

Lead GTM strategy and product positioning for key products, create messaging and content, run campaigns and launches, analyze market and competitive trends, and collaborate cross-functionally to drive adoption, pipeline growth, and customer engagement.

As the Director of Data Science, you'll mentor teams, oversee projects, drive data-driven decisions, and implement AI and ML solutions while enhancing our data pipeline.

As a Software Engineer, you will design and develop applications, write clean code, engage in code reviews, optimize systems, and explore new technologies in a remote team.

The Head of Compliance and Quality Governance will lead strategy, management, and operational execution of compliance within a biotech environment, ensuring adherence to regulations and promoting operational excellence.

Lead clinical data science workstreams across multiple low-to-moderately complex studies, develop and implement data management strategies, oversee data review and analysis, ensure regulatory compliance and data quality, provide stakeholder guidance, manage timelines/resources/financials, and mentor less experienced colleagues.

The role involves credit risk data analysis, report creation, and model monitoring with responsibilities varying based on experience level. Senior positions include designing data marts and preparing reports.

The Technology Recruiter will manage the end-to-end hiring process for engineering roles, develop sourcing strategies, assess candidates, and strengthen the employer brand while ensuring an exceptional candidate experience.

The Lead Golang Software Engineer develops server solutions, leads technical designs and code reviews, mentors colleagues, and ensures the quality of engineering practices in the Commercial Systems unit.

Oversee product strategy and development in EdTech and AI, manage teams, and drive data-informed decisions aligned with business goals.

Design, develop, and deploy production-grade ML and AI solutions including LLM fine-tuning, RAG architectures, NLP pipelines, time-series forecasting, supplier risk and anomaly detection, scalable data pipelines, and RESTful integrations with enterprise systems.

Lead clinical data science across global trials: own EDC builds, integrations, UAT, data documentation, cleaning, vendor reconciliation, and database locks while ensuring CDISC/ICH-GCP compliance, driving innovation, managing risks, and partnering with sponsors and cross-functional teams to deliver regulatory-ready data.

The role involves leading a team of Data Science Engineers to develop sports analytics and predictive models, ensuring high quality of data science workflows and collaboration with the Engineering Manager.

The Principal Data Science Engineer will leverage statistical analysis and machine learning to optimize airline revenue performance and customer experience, collaborating with teams to develop data models and algorithms, and support product development cycles.

Data Scientists at QuantCo will analyze data, build machine learning models, and communicate results to stakeholders, aiming for impactful solutions.

Lead hands-on credit-risk analytics: validate anonymized enterprise data, build PD/delinquency/scorecard models, establish model-validation and documentation, define features in SQL/dbt/Python, prototype a natural-language insight layer, and lead a small delivery pod while presenting findings to executives.

As a Data Science Intern, you'll identify frameworks for data-driven business challenges, transform datasets, run analyses, build machine learning models, and communicate results.