Director of Data Science, SmarterDx

• 10+ years of experience in data science, machine learning, or a related field, including significant people leadership responsibility
• Proven experience owning outcomes across multiple teams or product areas
• Track record of influencing executive stakeholders and shaping company strategy
• Deep expertise in machine learning fundamentals, with demonstrated ability to architect ML systems and set technical direction for senior teams
• Experience with NLP and healthcare data, including structured and unstructured clinical text
• Deep understanding of model evaluation, monitoring, experimentation, and real-world feedback loops
• Familiarity with modern ML platforms, cloud infrastructure, and MLOps best practices
• Demonstrated ability to connect technical work to revenue, margin, and customer outcomes
• Exceptional communication skills, with the ability to translate complex technical concepts for non-technical audiences
• Strong judgment in balancing speed, rigor, and long-term scalability

Desirable

• As Director of Data Science at SmarterDx, you will own the direction and impact of data science across multiple product areas within our Clinical AI platform at a moment of rapid product and company growth
• You will translate company strategy into clear priorities and lead teams responsible for production machine learning systems that directly shape clinical workflows and business outcomes
• This role blends technical and people leadership with close partnership across Product, Engineering, and Clinical teams
• You will set modeling and quality standards, develop managers and senior individual contributors, and guide machine learning systems from concept through responsible deployment in real healthcare environments, building reliable systems and teams that customers and clinicians depend on
• Own and evolve the Data Science strategy across multiple product areas, translating company and product objectives into a clear, prioritized roadmap with measurable business impact
• Drive portfolio-level prioritization, balancing near-term delivery with longer-term platform and capability investments
• Set technical direction and standards for production ML systems, with end-to-end ownership from problem framing and data strategy through deployment, monitoring, and iteration
• Partner closely with Product, Engineering, Clinical, and Operations leaders to embed data science into product workflows and decision-making
• Represent Data Science in product planning and executive forums, communicating tradeoffs, risks, and impact to senior stakeholders
• Lead and scale the Data Science organization, including managers, senior ICs, and emerging leaders, with clear expectations and ownership
• Own hiring, onboarding, and talent development, building durable career paths and a high-performing organization
• Champion responsible, interpretable, and clinically sound AI, ensuring models are appropriate for healthcare use and real-world deployment