Data Scientist (Mathematical Optimization)

PROJECT INFORMATION:

• Industry: Pharma

• Work model: Remote

Digital Warsaw HUB - Optimization

Are you ready to make a significant impact in the world of Data Science? We are looking for a Senior Data Scientist with strong expertise in Mathematical Optimization and Operations Research to join our Data Assets, Analytics and AI Platform team. In this role, you will take end-to-end ownership of optimization-driven solutions supporting global Product Supply and Supply Chain initiatives.

Our diverse, international team is responsible for managing the full product lifecycle – from problem definition and proof of concept to fully industrialized, production-ready solutions. We deliver business-critical decision-support systems based on mathematical optimization, forecasting and advanced analytics, leveraging a modern tech stack including Python, Azure and Databricks.

If you thrive in ambiguous environments, enjoy working closely with business stakeholders, and want to actively shape solutions rather than just execute tasks – we would love to hear from you.

Main Responsibilities

• Take ownership of end-to-end optimization solutions, from understanding and framing business problems to designing, implementing and maintaining production-grade models.

• Design, implement and evaluate mathematical optimization models (e.g. LP, MIP, potentially stochastic programming), as well as time series forecasting and machine learning models to support Product Supply and Supply Chain decision-making.

• Translate complex business challenges (e.g. production planning, capacity allocation, resource constraints) into well-formulated optimization problems with clear decision variables, objective functions and constraints.

• Build and validate optimization prototypes using Python-based modeling libraries (e.g. Pyomo, PuLP, OR-Tools, SciPy) and integrate them with appropriate solvers (e.g. Gurobi, HiGHS, CBC).

• Industrialize and scale successful advanced analytics and optimization prototypes into robust IT products.

• Maintain, enhance and continuously improve existing solutions to ensure performance, reliability and long-term scalability.

• Collaborate closely with international stakeholders, product owners and technical teams to co-create solutions and drive business impact.

• Analyze large structured and unstructured datasets to identify key drivers influencing product supply and operational performance.

• Build data processing pipelines and support data preparation for modeling and analytics.

• Create clear visualizations, dashboards and reports to communicate complex optimization outcomes and scenarios to both technical and non-technical audiences.

• Contribute to reusable frameworks, libraries and best practices for optimization and advanced analytics.

• Actively mentor team members and foster a culture of continuous learning within the data science community.

• Present data-driven insights and recommendations to various levels of the organization, including senior management.

• Act as a subject matter expert in mathematical optimization and Operations Research, advising on best practices and emerging approaches.

Key Requirements

• Master’s or PhD degree in Mathematics, Operations Research, Statistics, Computer Science, Engineering or a related quantitative field.

• Minimum 5 years of hands-on, commercial experience in Data Science, Operations Research or mathematical optimization.

• Proven experience designing and implementing mathematical optimization models (LP, MIP; experience with stochastic or advanced optimization is a plus), preferably in Supply Chain, manufacturing, logistics or production planning domains.

• Strong proficiency in Python, including optimization and analytics libraries (e.g. Pyomo, PuLP, OR-Tools, SciPy).

• Experience working with optimization solvers such as Gurobi, HiGHS, CBC or similar.

• Ability to write production-grade, maintainable code using object-oriented programming principles.

• Experience developing and deploying advanced analytics solutions in a cloud environment (Azure preferred).

• Strong problem-solving skills and the ability to work effectively in environments with evolving and not fully specified requirements.

• Excellent communication skills and proven ability to collaborate with international teams and business stakeholders.

• Fluent English, both written and spoken.

Nice to Have

• Experience with big data technologies and distributed data processing frameworks.

• Familiarity with Agile / Scrum ways of working.

• Exposure to simulation, scenario analysis or hybrid approaches combining optimization and machine learning.

• Experience mentoring junior team members or leading analytical initiatives.