Forward-Deployed Solutions Data Scientist

Waymark is a team of healthcare providers, technologists, and builders whose mission is to bring the best healthcare to people with Medicaid benefits. Guided by the communities we serve, we bring support and technology-enabled care to help primary care providers keep Medicaid patients healthy. We are building the tools and designing an approach to enable care to reach the patients who can benefit most.

Our core values embody the essence of what makes Waymark a unique team today, and what we look for, nurture, and sustain as a team. We are bold builders, believing that the greatest challenges in care delivery can be solved when we harness the power of community and technology. We are humble learners, seeking feedback and perspectives different from our own, and welcome challenges to our conclusions. We experiment to improve, actively seeking data to inform decisions and assess our own performance. We act with focused urgency — our commitment to our mission drives us to tirelessly pursue results.

About This Role

Waymark is seeking a Forward-Deployed Solutions Data Scientist to bridge the gap between data science innovation and real-world implementation. As our risk prediction platform and related data science tools scale across multiple health plan and health system partners, we need a dedicated data scientist to own the technical lift of onboarding, productionizing models, and supporting live deployments.

This role embeds data science expertise directly into customer implementations. You’ll lead data onboarding, schema negotiation, and feature alignment for new customers; support SaaS deployments; and operationalize advanced tools related to ML and AI including reinforcement learning. You’ll also play a critical role in scaling our SaaS products, building infrastructure that makes implementations repeatable, clinically sound, and production-ready.

This is a highly versatile role for a data scientist who thrives at the intersection of technical execution, healthcare data expertise, and cross-functional collaboration. You’ll work closely with Implementation, Product, Engineering, and external partners, ensuring our innovations move from R&D to production with speed, rigor, and impact. This position reports directly to the VP of Data Science and AI.

Responsibilities

• Lead data onboarding and ingestion: Manage schema mapping, clinical feature alignment, and QA for new customer data; resolve ingestion issues for existing deployments.
• Align data infrastructure across DS tools: Build and maintain a unified data foundation across Data Science, Engineering, and Analytics to reduce duplication and enable scale.
• Operationalize DS innovations: Transition new tools such as maternal risk, HEDIS, and SARSA from prototypes into production pipelines, ensuring reliability and reusability.
• Scale Signal-as-a-Service: Build infrastructure to support both internal and external Signal implementations, including ingestion pipelines, tagging, cohort logic, and metrics alignment.
• Support live Signal-only deployments: Own production support, including QA cycles, tagging updates, bug fixes, enhancements, and ROI tracking.
• Build and scale: Design and deploy targeting logic to improve existing risk models, enabling more precise and clinically actionable predictions.
• Serve as a senior DS generalist: Flex across implementation, infrastructure, and model development, bringing deep claims, health economics, and healthcare data expertise to critical delivery needs.

Minimum Qualifications

• Education: Master’s degree in Data Science, Computer Science, Biostatistics, or a related field.
• Python Proficiency: 5+ years of hands-on experience in Python, including data science and ML libraries.
• Healthcare Data Expertise: Strong background in claims data, clinical feature engineering, and healthcare workflows.
• Applied ML/AI Experience: Demonstrated ability to build, tune, and deploy ML models, including predictive modeling and patient segmentation.
• Implementation Skills: Experience leading data onboarding, schema negotiations, or large-scale data integrations in healthcare settings.
• Project Ownership: Proven ability to manage complex projects independently, align with multiple stakeholders, and deliver on timelines.
• Collaboration: Track record of thriving in cross-functional teams and working directly with customer-facing teams.

Preferred Qualifications

• Experience with novel AI causal inference methods and rei