(Senior) Data Scientist (w/m/d)

As a (Senior) Data Scientist in Advanced Analytics, you will be responsible for the performance and continuous improvement of mission-critical prescriptive analytics that directly impact daily decision making across procurement, inventory, supply chain, and portfolio management teams. Additionally, you will extend our team’s quantitative capabilities to develop and deliver data science solutions grounded in math, statistics and machine learning that drive real impact across Abacus Medicine Group.

Specifically, your main responsibilities will include:

• Owning the implementation and continuous improvement of prescriptive models that drive inventory and procurement decisions across Abacus Medicine’s pharmaceutical trading activities.
• Working directly with traders to formulate complex business challenges as clear quantitative problem formulations and to explain in business terms the recommended solutions.
• Collaborating across product, data, engineering, and business teams to turn advanced analytics models into well-architected, production-ready decision-support tools.
• Extending our optimization and decision science capabilities with new approaches (i.e. stochastic modelling) and into new domains (i.e. pricing and demand forecasting).
• Advancing the broader Data, Analytics & AI roadmap by taking ownership of internal technical initiatives that improve how we build and operate our analytical services.

Fuel for your success in the role

To be successful in this role, you bring:

• 2-5 years of applied experience as a Data Scientist or machine learning practitioner from an industry or enterprise environment where analytical models have been used to solve real business challenges.
• Practical experience and expertise in advanced quantitative methods, such as machine learning, mathematical modelling, optimization, simulation, operations research, or similar disciplines.
• Hands-on experience across the data science model lifecycle, including development, deployment, maintenance, and continuous improvement. Ideally, you are comfortable discussing end-to-end solution designs and architecture, and you have experience integrating predictive/prescriptive analytics into operational tools or workflows.
• Expertise in the data science tool stack including Python (pandas, numpy, scikit-learn, etc.), SQL proficiency for data wrangling, and software engineering tools such as git and Docker.
• Strong analytics translation skills and problem-solving frameworks that can turn ambiguous business requirements or complex challenges into clear analytical questions, solution designs, and ultimately business impact.
• A collaborative team-player mindset with effective and proactive communications. You know that enterprise data science doesn’t succeed on its own, and you are comfortable working with diverse business and technical roles in a fast-paced international setting.
• Fluency in English, both written and spoken.

You will have an advantage if you have particular expertise or experience with the following subjects:

• Applied operations research or optimization modelling in an enterprise setting for inventory or procurement decisions including experience Python-based solvers such as cvxpy or PuLP.
• Deep learning or reinforcement learning frameworks (i.e. PyTorch, TensorFlow) for decision-making, recommendation, or optimization use cases.
• Modelling uncertainty or stochasticity in an economic or operations context, such as price/supply/demand forecasting or inventory management.
• Developing and deploying data science models from a cloud environment. We work primarily in Azure Databricks, but value experience from other similar cloud stacks (AWS, GCP, ect.).
• AI/Agentic developer tools such as Claude Code or Github Copilot. We use AI tools to scale our human potential, not replace it.

Are you ready to embark on this journey with us?