Synthetic Population Engineer
Epistemix • US
Posted: December 8, 2025
Job Description
The Synthetic Population Engineer uses cutting edge data science techniques to continuously improve the Epistemix synthetic population. A synthetic population is a statistically representative model of a population of real people and their environment, including personal attributes, social connections, and associations between people and places. These datasets empower customers to solve problems in domains where empirical data is unavailable due to legitimate concerns for personal privacy or where desired data simply does not exist. The Synthetic Population Engineer contributes to profitable growth by making the synthetic population more useful and accessible to customers, increasing adoption and utilization. Having a synthetic population that is continuously updated and improved over time is critical to building trust in the models and solutions built with our platform.
About Epistemix
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.
Responsibilities
Identify and evaluate empirical datasets and use them to enrich the synthetic population to enable new use cases, including through adding new individual attributes and detailed social networks.
Utilize simulation techniques, including ABMs, to project future demographic trends.
Improve the geographical plausibility of synthetic environments, ensuring realistic placement of homes, workplaces, schools, and other points of interest (e.g., along roads, close to real world population centers).
Expand the geographical region covered by the Epistemix synthetic population, with the goal of creating a fully integrated and consistent representation of the global population.
Create visualizations for marketing and productizing synthetic populations.
Develop innovative methods for supporting external users in augmenting Epistemix synthetic populations with their own proprietary data.
Work with external vendors and marketplaces to expand the ecosystem of data providers that can be integrated with the synthetic population.
Support the synthetic populations team in engaging with customer success, professional services, and engineering teams to understand project specific synthetic population requirements.
Qualifications
Proficient experience in:
Using Python for data science applications.
Working with relational databases such as PostgreSQL (additional database management experience preferred).
Working with geospatial data.
Working with simulation or machine learning models.
Demonstrate empathy for users and decision makers by explaining how the synthetic population was created (e.g., which data sources and models were used) in an accessible way for all.
Possessing the passion to build the standard for synthetic populations globally to improve decision making across social, health, economic, and environmental policies and advancing data science into more commercial applications.
A PhD or master’s degree in Data Science or a relevant technical discipline such as Computer Science, Mathematics, Statistics, Epidemiology, or Public Health.
Proven track record of success building data products and/or data marketplaces.
Having a startup mentality with understanding the risks and the ability to flex across needs of an evolving team in a fast-paced environment.
Why Join Epistemix?
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.
This is a remote position open to applicants globally with a strong interest in US and Europe based candidates . Candidates must possess the legal right to work in their intended work location, as we are currently unable to sponsor or transfer employment visas for any country, including the United States.
Additional Content
The Synthetic Population Engineer uses cutting edge data science techniques to continuously improve the Epistemix synthetic population. A synthetic population is a statistically representative model of a population of real people and their environment, including personal attributes, social connections, and associations between people and places. These datasets empower customers to solve problems in domains where empirical data is unavailable due to legitimate concerns for personal privacy or where desired data simply does not exist. The Synthetic Population Engineer contributes to profitable growth by making the synthetic population more useful and accessible to customers, increasing adoption and utilization. Having a synthetic population that is continuously updated and improved over time is critical to building trust in the models and solutions built with our platform.
About Epistemix
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.
Responsibilities
Identify and evaluate empirical datasets and use them to enrich the synthetic population to enable new use cases, including through adding new individual attributes and detailed social networks.
Utilize simulation techniques, including ABMs, to project future demographic trends.
Improve the geographical plausibility of synthetic environments, ensuring realistic placement of homes, workplaces, schools, and other points of interest (e.g., along roads, close to real world population centers).
Expand the geographical region covered by the Epistemix synthetic population, with the goal of creating a fully integrated and consistent representation of the global population.
Create visualizations for marketing and productizing synthetic populations.
Develop innovative methods for supporting external users in augmenting Epistemix synthetic populations with their own proprietary data.
Work with external vendors and marketplaces to expand the ecosystem of data providers that can be integrated with the synthetic population.
Support the synthetic populations team in engaging with customer success, professional services, and engineering teams to understand project specific synthetic population requirements.
Qualifications
Proficient experience in:
Using Python for data science applications.
Working with relational databases such as PostgreSQL (additional database management experience preferred).
Working with geospatial data.
Working with simulation or machine learning models.
Demonstrate empathy for users and decision makers by explaining how the synthetic population was created (e.g., which data sources and models were used) in an accessible way for all.
Possessing the passion to build the standard for synthetic populations globally to improve decision making across social, health, economic, and environmental policies and advancing data science into more commercial applications.
A PhD or master’s degree in Data Science or a relevant technical discipline such as Computer Science, Mathematics, Statistics, Epidemiology, or Public Health.
Proven track record of success building data products and/or data marketplaces.
Having a startup mentality with understanding the risks and the ability to flex across needs of an evolving team in a fast-paced environment.
Why Join Epistemix?
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.
This is a remote position open to applicants globally with a strong interest in US and Europe based candidates . Candidates must possess the legal right to work in their intended work location, as we are currently unable to sponsor or transfer employment visas for any country, including the United States.