Data Scientist

Support customers’ and colleagues’ efforts to use our platform to deliver data integration, visualizations, models and recommendations that create meaningful impact

• Work with customer teams to understand their goals and help develop data integration, modeling, and visualization plans to support decision making
• Collaborate with customer and internal teams to develop, test, and validate simulation models, ensuring their accuracy and relevance for healthcare use cases
• Provide guidance for proposals on feasibility of scope and how to ensure impact
• Contribute to customer onboarding experiences and content, helping to ensure customers quickly achieve their first successes with the platform
• Engage with customer users to provide informal support, tips, and troubleshooting
• Collaborate with premium support customers by integrating data and creating models, simulations, or visualizations. Support recommendation development and action plans
• Participate in reviews with customers to document and improve measurable impact
• Provide feedback to Product and Sales teams to align offerings with customer needs
• Follow advancements in data science, machine learning, and healthcare analytics

• Commitment to understanding customer needs and helping them achieve goals
• Creative mindset with a passion for tackling challenging problems with data
• Ability to collaborate with diverse users and internal teams
• Strong communication skills: verbal, code, visualizations, and maps
• Strong foundation in machine learning, data modeling, and predictive analytics
• Understanding of key concepts of the healthcare industry required. Prior healthcare experience (broadly defined) very strongly preferred
• Comfort working in a dynamic environment with evolving priorities and customer needs
• Proficiency in Python and associated data science technologies
• Experience with data visualization tools such as Tableau, Power BI, and/or GIS tools
• Expertise in SQL or NoSQL databases preferred
• 2-3 years prior experience as a Data Scientist, Analyst, or similar role, with demonstrated ability to solve complex data challenges. (Work in PhD program can count toward experience)
• Masters or Ph.D in Data Science, Computer Science, Epidemiology, Economics, Public Health, Statistics, Mathematics, or similar quantitative field
• Experience with more than one company size or business stage preferred
• Must be legally authorized to work in the United States and not require employer sponsorship now or in the future.

By joining Epistemix, you will become part of a collaborative and rapidly growing team that values curiosity and creativity. We are fully remote, with team members in the United States and Europe. Benefits include:

• Equity & Incentives - Participation in our stock option program.
• Flexible Time Off - Autonomy to manage your schedule and work-life balance.
• Health, Welfare and 401(k) Programs - Eligibility for benefits (for U.S. employees).
• Meaningful Impact - Apply your creative talents to revolutionize data-driven decision-making and make a real-world difference.

The most consequential decisions in public health, life sciences, insurance, and enterprise strategy share a common problem: they involve human behavior, network effects, and downstream effects that cannot be safely tested before action is taken. Traditional analytical techniques built on historical data were not built for this. Epistemix was.

We build simulation and data-driven modeling tools that let leaders visualize how strategies will unfold across populations and systems before they commit resources. By clarifying which variables drive outcomes, where leverage exists, and how they interact, we help organizations move from uncertainty to conviction. Getting these decisions right means faster interventions, better-allocated resources, and measurable improvements in human and economic outcomes. We exist to make that possible.

Our platform gives organizations access to realistic, high-resolution population data and the modeling infrastructure to run scenario planning at scale. Together, these capabilities let decision-makers stress-test strategies in a controlled environment before deploying them in the real world across healthcare, consumer industries, insurance, and government. We are approaching our Series B and actively building the team that will define what comes next.