Staff Applied Scientist

Responsibilities

• Own ambiguous, high-stakes algorithmic problems end-to-end, setting how the team frames and approaches them.
• Translate healthcare and business constraints into clear objectives, tradeoffs, and decision frameworks.
• Define metrics to evaluate solutions and validate them before production release.
• Select appropriate approaches, including machine learning, optimization, heuristics, expert systems, and simpler rules.
• Deliver algorithmic improvements that advance important company metrics.
• Lead a small team by setting technical direction, removing blockers, and supporting growth and quality.
• Review Applied Science work across the company for methodological rigor and correct application.
• Build a deep understanding of the healthcare economy and the company’s role within it.
• Work from the New York City office three days per week, Tuesday through Thursday.

Near-Term Projects

• Develop provider-tiering optimization that balances geographic access and total-cost-of-care savings.
• Fine-tune and productionize an LLM-based primary-care experience, including evaluation, guardrails, and quality monitoring.
• Build a member-engagement model using claims data and in-app behavior to select the appropriate communication channel and timing.

Requirements

• 6+ years of industry experience as an Applied Scientist, Machine Learning Engineer, Research Scientist, or equivalent; or 4+ years with a relevant advanced degree. PhDs preferred.
• Strong applied problem-solving skills and the ability to define metrics and deliver solutions that improve them.
• Recognized technical authority and sound judgment in applying technical methods.
• Strong judgment when choosing among statistical models, heuristics, optimization, and simpler algorithmic methods.
• Strong communication skills, including executive-level communication and organization-wide alignment.
• Interest in mentoring or technically leading other scientists; formal management experience is welcome but not required.
• Bias toward action and ability to quickly turn ideas into working prototypes.

Technologies

• Python
• SQL
• AWS
• Snowflake
• pandas
• XGBoost
• PyTorch
• Hugging Face
• Modern LLM tooling and evaluation frameworks

Compensation and Benefits

• Target base compensation: $300,000–$390,000.
• Equity incentive eligibility.
• Flexible paid time off.
• Medical, dental, and vision plan options.
• 401(k) with company match.
• Flexible spending accounts.
• Teladoc Health and other benefits.