Epistemix

Operations

• Support the COO in designing and maintaining internal systems that enable the organization to operate effectively.
• Maintain key internal resources so critical information, decisions, and processes remain visible, searchable, and easy for teams to navigate as the company grows.
• Partner with the COO to lead internal initiatives, introducing improved ways of working, and supporting teams as new systems or operational practices are implemented.
• Oversee the day-to-day operational management of company technology systems, including employee access, licensing, and basic infrastructure coordination.
• Manage vendor relationships, prioritize requests, and ensure timely resolution of technology issues while maintaining high standards for responsiveness, reliability, and service quality.
• Serve as a key operational partner to the COO in maintaining financial visibility across the organization.
• Assist the COO in supporting the organization’s commitment to disciplined financial management by monitoring spending across teams and ensuring financial practices remain consistent with company priorities.
• Support the COO in coordinating the operational rhythm of the enterprise, leadership team and board engagement cycles.
• Help maintain focus by supporting the coordination of leadership priorities and schedules.
• Coordinate the planning and execution of key company moments including leadership offsites, company gatherings, and industry events.
• Support high-priority initiatives led by the COO and leadership team by stepping in to advance urgent or complex workstreams, gathering information across teams, and ensuring important initiatives continue to move forward.

Manager, Strategic Operations

Infrastructure Engineer

• Design and execute the technical strategy for integrating the Epistemix platform into client environments.
• Leverage Terraform, Kubernetes and Docker across client environments, ensuring security and repeatability with a primary focus on AWS and data connections like Snowflake and Databricks.
• Interface with client IT organization to understand infrastructure environment and provide architectural guidance during implementation.
• Ensure all client-side integration and deployment methods are designed to meet rigorous standards, including SOC 2 and ISO 27001, HIPAA.
• Work with client IT organizations to set deployments in complex settings, including public cloud (AWS/GCP), private cloud, and traditional on-premises/dedicated application environments.
• Develop and use custom automation tooling (Python is a must) to streamline deployment processes, integrating with client-side identity and access management (e.g., OAuth2/OIDC).

Infrastructure Architect

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

Backend Engineer

• Design, develop, and maintain clean, testable, and highly maintainable code, ensuring top-tier performance and reliability.
• From initial requirements gathering to deployment and ongoing maintenance, take full ownership of the software development lifecycle, ensuring seamless delivery and operation.
• Design, build, test and deploy a highly scalable and resilient system architecture that supports current needs and future growth.
• Define the technical direction for engineering solutions, actively collaborating with internal teams to ensure technological advancements are perfectly aligned with the company's strategic goals.

Senior Back End Software Engineer

Engineer

• 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.

Synthetic Population Engineer

Account Executive

• Consistently develop and qualify opportunities for new business.
• Establish key messaging by vertical and accounts to accelerate the sales cycle.
• Network with decision makers and other key opinion leaders to identify opportunities.
• Communicate with CEO and CPO on a regular basis to refine the go-to-market motion within your vertical.
• Collaborate with Sales Engineers to build demos.
• Collaborate with Solution Architects to complete scopes of work.
• Collaborate with the CEO to close large accounts.
• Communicate valuable feedback from prospects with the go-to-market team.
• Be a steward of the Epistemix brand.

Strategic Account Executive

Solutions Engineer

• Accelerate sales qualified leads to contracting; increase net-revenue retention; increase recurring revenue.
• Own and execute the process to develop scopes of work (SOWs) alongside sales, customer success, and product.
• Partner closely with the CEO, CPO, and customer success to understand customer needs and our product roadmap to deliver high quality SOWs that meet customer needs aligned to the products our team has developed and/or is developing.
• Translate customer needs into clear, actionable proposals, developing statements of work and guiding strategic discussions that blend technical depth with creative problem-solving.
• Engage with sales qualified leads (SQLs) to lead discovery sessions and understand technical, data, and strategic needs of customers.
• Architect solutions that align Epistemix’s capabilities with client use cases, goals, and constraints.
• Draft statements of work (SOWs), including technical scope, deliverables, timelines, and level of effort.
• Act as a subject matter expert on Epistemix’s data platform and modeling tools in customer conversations.
• Collaborate closely with Sales, Product, and Customer Success to shape and scope engagements.
• Maintain a strong understanding of Epistemix’s product roadmap to shape how future capabilities can meet client needs.
• Ensure seamless handoffs from pre-sales to delivery teams, including documentation and context transfer.
• Develop tooling to support Sales Engineers’ ability to prototype solutions that enable you to scope work more efficiently.

Solution Architect

AI Engineer

• Craft clean, testable, and maintainable code to enable AI-generated agent-based models.
• Own the software from requirements development through deployment and maintenance that enable decision makers to generate agent-based models that address critical business questions and data scientists to build agent-based models more quickly that answer the questions of decision makers.
• Design, build, test, and deploy a scalable system architecture so that AI-generated models can be validated by data scientists and deliver results back to decision makers quickly.
• Own the engineering solution and collaborate with internal teams to ensure alignment with company strategy.