Senior Applied Scientist

About the Role:

We are seeking an exceptional Senior Applied Scientist to join our Applied Science team. In this role, you will design, develop, and deploy the algorithmic systems that power Garner's products and drive meaningful impact for our members. Our members rely on us to answer hard questions — Which doctor should I see? What will it cost? When should we reach out, and how? — and the quality of those answers is determined by the algorithms behind them.

This is not a dashboards or descriptive-analytics role. You will own production systems end-to-end: framing the problem, defining the objective function, choosing the right approach (ML, optimization, heuristics, expert systems, or a hybrid), shipping it, and improving it against real-world outcomes. The closest analog outside healthcare is a quantitative researcher at a top hedge fund.

What you will do:

• Own the design, performance, and evolution of the algorithms that power Garner’s core systems
• Turn messy, real-world healthcare and business constraints into clear optimization problems, scoring systems, and decision frameworks
• Develop objective functions and metrics that balance quality, cost, access, and member experience
• Evaluate system performance, run experiments, and refine logic based on real-world outcomes
• Apply machine learning, optimization, heuristics, or rules-based approaches based on what best solves the problem
• Work closely with engineering to deploy systems that are scalable, interpretable, and resilient
• Build a deep understanding of the healthcare economy

The ideal candidate has:

• 4+ years of industry experience as an Applied Scientist, Machine Learning Engineer, Research Scientist, or equivalent; or 3+ years of industry experience with a relevant advanced degree (PhDs preferred)
• Demonstrated ability to move quickly from concept to execution, building prototypes to and running experiments to validate ideas and accelerate learning.
• Strong analytical and problem-solving skills, with experience identifying meaningful success metrics and delivering solutions that drive measurable improvements 
• Sound technical judgment in choosing between statistical models, heuristics, optimization approaches, and simpler algorithmic methods depending on the problem
• Excellent communication skills and the ability to synthesize complex algorithmic ideas for business and technical stakeholders
• A desire to be a part of a high-performing, mission-driven team that operates with urgency, a strong sense of individual accountability, and a commitment to authentic feedback

Technologies we use: 

• Python, SQL, AWS, Snowflake, pandas, XGBoost, PyTorch, HuggingFace, modern LLM tooling and eval frameworks. We pick tools based on the problem, not the resume — bring your judgment.

This is a unique opportunity to join a fast-growing company in a transformative role, helping shape the future of healthcare.

Compensation Transparency:

The target base comp range for this position is $236,000 – $260,000. Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k) with company match, flexible spending accounts, Teladoc Health and more.