Principal Applied Machine Learning Scientist

This is a fully remote position, open to applicants in California, +2 more states.

📋 Description

• Oversee the research and development of models that forecast individual and population health trajectories, utilizing complex, real-world longitudinal healthcare data to predict future states, risks, and progression paths.

• Generate high-quality experimental evidence and provide technical recommendations that pave the way for impactful product features, significantly influencing both individual and population health trajectories.

• Direct the creation of next-best-action algorithms that transform predicted health trajectories into tailored intervention decisions based on a member's current situation and anticipated future path.

• Investigate and implement advanced decision-making and recommendation policies to effectively optimize intervention selections within the healthcare context.

• Establish objective functions, reward signals, and policy constraints that balance factors such as engagement, clinical effectiveness, fairness, and operational feasibility, collaborating with product and clinical teams to ensure that outputs are actionable and comprehensible.

• Act as the senior scientific authority on algorithmic integrity and evaluation rigor related to trajectories and next-best-action, defining standards for problem formulation, assessment, and publication-quality analysis.

• Guide and mentor other scientists and data scientists in advanced techniques in temporal modeling, reinforcement learning, and causal inference.

• Work in close collaboration with platform, MLOps, and product engineering teams to guarantee that research outcomes can be reliably integrated into production and monitored effectively.

⛳️ Requirements

• A Ph.D. in Computer Science, Statistics, Machine Learning, Biostatistics, Applied Mathematics, or a related quantitative field is mandatory; a Master's degree with significant, relevant experience at a senior level may also be considered.

• Several years of experience in machine learning research or applied research science at the post-secondary level, with a proven track record of delivering innovative algorithms or impactful ML systems in production.

• Profound expertise in time-series or longitudinal modeling, healthcare prediction, recommender systems, reinforcement learning, causal inference, or closely related research domains pertinent to trajectories and next-best-action decision-making.

• Strong skills in Python and contemporary ML tools, along with experience deploying models in production settings on cloud platforms such as AWS SageMaker or similar.

• Proven capability to convert vague business inquiries into well-defined technical challenges, effectively communicate trade-offs to non-technical stakeholders, and integrate feedback into model and metric development.

🏝️ Benefits

• Competitive salary paired with a generous annual cash bonus.

• Equity grants.

• A remote-first work-from-home culture.

• Flexible Time Off to help you rest, recharge, and connect with family and friends.

• Generous parental leave.

• Comprehensive health, dental, and vision insurance with above-market employer contributions.

• 401k retirement savings plan.

• Lifestyle Spending Account (LSA).

• Mental Health Support Solutions.

• ...and more!