About the Role
A growing healthcare data science team is seeking a Data Scientist to help develop and implement core methodologies and software solutions. The team’s platform predicts the clinical, social, and commercial value of new medical technologies in the real world to optimize risk-sharing, advance market access, improve evidence-generation investments, and accurately assess commercial value.
This position is ideal for candidates with a Master’s or PhD in Engineering or Computer Science (or similar field). Applicants should have experience with simulation modeling, statistics, machine learning, and/or health economics. Software Engineering is a huge plus!
The Data Scientist will build robust data pipelines, perform exploratory and advanced data analyses, implement statistical and machine learning algorithms, and use simulation techniques to support decision-making. They will also contribute to internal software libraries and support client projects as part of a consulting team. The ideal candidate is collaborative, intellectually curious, and eager to continue learning. Strong communication skills—both written and verbal—are essential, along with excellent technical abilities.
Responsibilities
- Develop cost-effectiveness simulation models and apply advanced value assessment techniques to estimate the social value of medical technologies
- Use microsimulation to forecast the commercial value of new medicines and evaluate outcomes-based contracts
- Collaborate with data engineers to build data pipelines that process real-world datasets (e.g., medical claims, electronic health records) or clinical trial data
- Implement probabilistic statistical and machine learning models to predict health and financial outcomes, estimate causal effects, and quantify uncertainty
- Build web applications and interactive reports to enable clients to run and interact with models
- Contribute to internal software libraries by adding new modeling features, creating unit tests, writing documentation, and ensuring adherence to style conventions
- Follow software best practices, including version control (Git), code review, continuous integration, and continuous deployment
- Communicate results and methodologies clearly to internal teams and external clients
Qualifications
- Master’s or PhD in Engineering, Software Engineering, or Computer Science
- Fluency in Python or R
- Familiarity with SQL
- Experience writing technical documents, reports, manuscripts, or presentations
- For Senior Data Scientist candidates: 2–4 years of relevant work experience