About The Position

The Solutions Lead, Assessments will shape and deliver healthcare AI assessments around the decisions customers need to make. The role translates customer needs into feasible scopes and owns delivery across DataLab, engineering, verification, and data partners, from initial feasibility through customer acceptance. This position combines solution design, hands-on delivery, and strategic judgment. It weighs trade-offs across data sources, evaluation approaches, and capacity; recommends priorities and reusable investments; stays close to technical work to challenge assumptions and troubleshoot dependencies; and turns delivery experience into playbooks and better operating decisions. The role is expected to establish a delivery cadence, lead assigned customer deliveries, improve delivery performance against a baseline, make playbooks usable by teammates, and recommend a prioritized roadmap of process or tooling investments.

Requirements

  • Experience shaping and delivering complex customer or partner engagements by translating ambiguous needs into feasible solutions and concrete outcomes.
  • Experience coordinating technical, operational, and external stakeholders, clarifying dependencies and decision ownership without relying on direct authority.
  • Ability to manage changing requirements and difficult timelines while maintaining clear expectations and customer trust.
  • Experience building a playbook or operating process that others adopted, with evidence that it reduced confusion, delay, or repeated work.
  • Ability to interpret technical evidence and work effectively with the specialists who produce it.

Nice To Haves

  • Experience working with healthcare data.
  • Experience with AI evaluations, ML products, or enterprise data delivery.
  • SQL, Python, and API tooling skills.

Responsibilities

  • Translate customer goals into assessment scopes, success criteria, and delivery plans with clear technical and commercial assumptions.
  • Coordinate DataLab, engineering, commercial teams, and data partners through each delivery stage.
  • Coordinate partner specifications and data-readiness checks across relevant EHR, claims, imaging, pathology, and text sources.
  • Serve as the primary delivery contact, making technical decisions, progress, risks, and trade-offs clear to customers.
  • Assess technical feasibility and recommend scope, source, or execution options based on customer value, effort, risk, and capacity.
  • Coordinate data-quality, privacy, scientific, and technical readiness reviews with responsible experts before work advances.
  • Manage changing requirements and competing projects, recommending priorities and communicating the impact on timing, effort, and deliverables.
  • Build reusable playbooks for intake, feasibility, QA, partner handoffs, escalation, and acceptance.
  • Use delivery evidence to prioritize process and tooling improvements, explaining expected customer value and capacity benefits.
  • Coordinate results delivery, customer acceptance, and handoff into the next assessment or rerun.
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