Manager, Applied Science
Leads and builds a team of Applied Scientists developing production algorithmic systems for healthcare optimization, LLM applications, and member engagement. Requires 6+ years of relevant industry experience, strong technical judgment, and hands-on expertise across machine learning and optimization.
About the job
Responsibilities
- Lead, hire, coach, and develop a team of Applied Scientists.
- Own the team's roadmap and delivery, including prioritization and shipping decisions.
- Set technical direction across machine learning, optimization, heuristics, expert systems, and hybrid approaches.
- Define metrics, validate solutions, and establish quality standards before and after deployment.
- Work hands-on on high-stakes, ambiguous algorithmic problems that improve healthcare cost savings, care steerage, and member engagement.
- Translate business goals into clear problem definitions with Research, Product, Engineering, and business stakeholders.
- Represent the team's work to senior leadership.
- Build a deep understanding of the healthcare economy and Garner's role within it.
Near-Term Problem Areas
- Optimize provider tiers for 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 member-engagement models using claims data and in-app behavior to select effective outreach channels 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.
- PhD preferred.
- Deep technical credibility and willingness to remain hands-on.
- Strong judgment in selecting statistical models, heuristics, optimization methods, and simpler algorithmic approaches.
- Strong applied problem-solving skills and ability to define and improve meaningful metrics.
- Bias toward action and ability to translate ideas into working prototypes.
- Strong communication skills, including executive-level communication and cross-functional alignment.
- Commitment to a high-performing, mission-driven, accountable, and feedback-oriented team.
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.
Skills
Python, SQL, AWS, Snowflake, pandas, Xgboost, PyTorch, Hugging Face, LLMs, Machine Learning, Optimization, Heuristics, Statistical Modeling, Evaluation Frameworks, Claims Data
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