Solutions Lead, Assessments

Role overview The Solutions Lead, Assessments shapes and delivers healthcare AI assessments around the decisions customers need to make. The role owns delivery from initial feasibility through customer acceptance, coordinating technical teams and data partners while balancing customer value, feasibility, risk, and available capacity. It also turns delivery experience into repeatable playbooks and practical improvements to processes and tools.

Responsibilities - Translate customer goals into assessment scope, success measures, delivery plans, and clear technical and commercial assumptions. - Coordinate engineering, data specialists, commercial teams, and external partners across each stage of delivery. - Align partner specifications and data-readiness checks for relevant electronic health record, claims, imaging, pathology, and text data. - Serve as the main delivery contact, explaining decisions, status, risks, and trade-offs to customers. - Assess feasibility and recommend scope, data source, or execution options based on value, effort, risk, and capacity. - Coordinate data quality, privacy, scientific, and technical readiness reviews with the responsible experts; manage changing requirements and competing priorities. - Create reusable processes for intake, feasibility, quality review, partner handoffs, escalation, and acceptance, then use delivery evidence to propose improvements.

Requirements - Experience delivering complex customer or partner engagements, turning ambiguous needs into feasible plans and concrete outcomes. - Ability to coordinate technical, operational, and external stakeholders, clarify dependencies, and establish decision ownership without relying on direct authority. - Experience handling changing requirements and challenging timelines while maintaining clear expectations and customer trust. - Track record of creating an operating process or playbook adopted by others and reducing confusion, delay, or repeated work. - Ability to interpret technical evidence and work effectively with specialists who produce it.

Nice to have Healthcare data experience is optional. Familiarity with AI evaluations, machine-learning products, or enterprise data delivery is useful; SQL, Python, and API tooling can help but are not required.

Benefits and work setup The role includes an initial delivery plan: understand customer decisions and dependencies in the first month; lead assigned work and test a playbook across projects by around 60 days; and, by around 90 days, bring a project to acceptance or an agreed checkpoint and recommend prioritized process or tooling investments.