Chief Data Scientist – AI Healthcare Technology

Clarify AI seeks a visionary Chief Data Scientist to lead our data science efforts and help shape the future of AI in healthcare. In this role, you’ll drive innovation, guide a high-performing team, and align data science strategy with business goals to transform how billing is understood and managed across the healthcare system.

• Define and lead Clarify AI’s data science and AI strategy, with a focus on innovation, impact, and scalability.
• Champion the responsible and ethical use of AI in healthcare, prioritizing transparency, fairness, and data privacy.
• Guide the development, testing, and deployment of machine learning models in collaboration with engineering and product teams.
• Oversee the design of scalable data pipelines and model deployment infrastructure to support both real-time and batch inference.
• Help data teams determine the best route for tackling use cases by assessing scope, selecting techniques, and evaluating trade-offs.
• Maintain visibility into data science initiatives across the organization to ensure alignment, progress, and measurable outcomes.
• Translate complex technical insights into clear, actionable updates for executive stakeholders and external partners.
• Collaborate cross-functionally with Product, Engineering, Clinical, Compliance, and Business Development teams to ensure solutions meet real-world needs.
• Translate cutting-edge AI research into practical applications that improve healthcare outcomes and simplify billing complexity.
• Drive enterprise-wide efforts to harness AI and analytics in streamlining healthcare delivery, administration, and cost management.
• Recruit, mentor, and develop a world-class data science team, fostering a culture of curiosity, rigor, and innovation.

• Master’s or PhD in Computer Science, Data Science, Statistics, or a related field.
• 10+ years of experience as a data scientist, with at least 3+ years in healthcare or healthtech preferred.
• Proven leadership in building and managing high-performing, multidisciplinary data teams.
• Deep expertise in statistics, machine learning, and AI, with hands-on experience in tools such as Python, R, TensorFlow, Keras, or PyTorch.
• Strong grasp of AI ethics, data governance, and privacy best practices, especially in healthcare contexts.
• Familiarity with healthcare data formats and standards (e.g., HL7, FHIR, X12) and regulatory requirements (e.g., HIPAA, CMS).
• Exceptional communication skills, with the ability to engage and influence both technical and non-technical stakeholders.
• Demonstrated critical thinking and a track record of structuring and solving complex, unstructured problems.
• Experience translating research and experimental models into production-grade solutions.
• Comfort working in a fast-paced, early-stage environment where adaptability and hands-on leadership are key.
• Experience engaging with employers, healthcare payers, health systems, and regulatory bodies is a strong plus.