Data Scientist

Data Scientist – Provider Network Analytics
Location: Remote (US)
About The Company
We are a mission-driven enterprise at the forefront of transforming how healthcare and benefits services are delivered across the country. Our teams operate at national scale, supporting billions in revenue and serving millions of individuals. We value innovation, financial impact, and seamless user experiences, and take a product-first approach to solving complex challenges through data and technology.
This role sits within the organization's provider network team, which shapes the networks of providers that members rely on for care. The team is building a data-driven decision support tool that helps network stakeholders answer a critical question: which providers belong in the performance network? It's a high-visibility product with direct influence on network strategy, and the people who join now will help shape how it grows.
Job Summary
We are seeking a Data Scientist to help build and evolve the analytics behind this decision support product. The work today is classic, applied data science: strong SQL and Python, large-scale querying in BigQuery, and turning complex provider data into clear, defensible recommendations for network stakeholders. Modeling is light for now, but that will change as the product matures. The roadmap includes more advanced work such as graph modeling of provider relationships and scenario modeling to test network configurations. This role suits someone who does the fundamentals well and wants to grow into more sophisticated methods.
Key Responsibilities
Data Analysis & Querying: Write efficient, well-structured SQL against large provider, claims, and performance datasets in BigQuery.
Python Development: Build analysis pipelines, data transformations, and reusable code in Python to power the decision support tool.
Provider Evaluation: Develop metrics and analytical frameworks that assess provider performance and inform which providers belong in the performance network.
Decision Support: Turn analytical findings into clear, actionable insights for network stakeholders, balancing rigor with practical usability.
Modeling Evolution: Contribute to more advanced approaches as the product matures, including graph modeling of provider relationships and scenario modeling to evaluate network design trade-offs.
Stakeholder Partnership: Work closely with network leaders and business partners to understand their decisions, refine requirements, and make sure the tool answers the right questions.
Data Quality & Documentation: Validate data, document methods, and keep analyses transparent and reproducible.
Requirements
Experience: 3+ years of hands-on experience in data science or advanced analytics roles.
SQL: Advanced SQL proficiency with large, complex datasets; BigQuery experience strongly preferred.
Python: Strong Python skills for data manipulation and analysis (e.g., pandas, NumPy).
Statistical Foundation: Solid grounding in core statistics and applied data science methods.
Communication: Ability to explain analytical work and recommendations clearly to non-technical stakeholders.
Work Style: Self-directed and comfortable working remotely in a product environment where scope and methods evolve over time.
Preferred Qualifications
Experience in healthcare, particularly provider networks, claims data, or provider performance analytics
Exposure to graph analytics or network modeling (e.g., NetworkX, graph databases)
Experience with scenario modeling, simulation, or optimization techniques
Experience building or supporting analytics products or decision support tools
Familiarity with Google Cloud Platform
Benefits
Competitive Salary: Market-aligned compensation
Health and Wellness: Access to a comprehensive benefits package
Work-Life Balance: Fully remote work environment with flexible hours and a supportive culture
Professional Development: Opportunity to work with a high-performing team with access to modern technologies and ongoing learning resources
Additional Perks: Inclusive work environment, long-term career potential, and involvement in high-impact projects

Work arrangement
Yes