Waymark

Product Adoption Specialist

• Serve as primary point of contact for end-users, ensuring smooth onboarding and ongoing support.
• Provide personalized training remotely and potentially in person to optimize user experience and proficiency.
• Build close, long-lasting relationships with customer contacts to ensure highest level of satisfaction.
• Organize and lead webinars and workshops on best practices, new features, and platform tips.
• Establish and maintain a customer feedback loop to gather insights and suggestions for product enhancements.
• Initiate proactive outreach to users who may be experiencing issues or have been inactive to re-engage them.
• Collaborate with Customer Success Managers and internal teams (Sales, Marketing, Creative, Product & Engineering).
• Work with CSMs to establish plans to achieve customer goals and drive adoption.
• Locate and curate success stories, generate case studies and testimonials to drive adoption.
• Respond to questions, feedback, or complaints with urgency and improve processes to prevent repeat issues.
• Act as a customer advocate focused on improving the customer experience.
• Report directly to the Senior Manager of Product Adoption.

Product Adoption Manager

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.
Bridge the gap between data science innovation and real-world implementation; own onboarding, productionizing models, and supporting live deployments.
Embed data science expertise directly into customer implementations; 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.
Work closely with Implementation, Product, Engineering, and external partners to move innovations from R&D to production.
Lead data onboarding and ingestion: manage schema mapping, clinical feature alignment, and QA for new customer data; resolve ingestion issues.
Align data infrastructure across DS tools: build and maintain a unified data foundation across Data Science, Engineering, and Analytics.
Operationalize DS innovations: transition tools such as maternal risk, HEDIS, and SARSA from prototypes into production pipelines.
Scale Signal-as-a-Service: build infrastructure for Signal implementations, including ingestion pipelines, tagging, cohort logic, and metrics alignment.
Support live Signal-only deployments: own production support, QA cycles, tagging updates, bug fixes, enhancements, and ROI tracking.
Build and scale: design and deploy targeting logic to improve risk models; enable precise and clinically actionable predictions.
Serve as a senior DS generalist: flex across implementation, infrastructure, and model development, bringing claims, health economics, and healthcare data expertise to delivery needs.

Product Adoption Manager

Forward-Deployed Solutions Data Scientist