Senior Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop and refine vendor-matching models that ascertain which vendor is best suited to fulfill each incoming order.

• Create predictive models to identify orders that may be at risk of delay based on historical data.

• Utilize established frameworks and methodologies to pinpoint and assess supply-chain bottlenecks.

• Implement and evaluate components of decision logic for agentic AI.

• Take ownership of models throughout their lifecycle, including vendor matching, order routing, and supply-chain optimization.

• Establish confidence thresholds and decision-making components for agentic AI.

• Measure the impact of your work using quantitative metrics.

• Transition models from experimentation to production in collaboration with data engineering.

• Apply predictive machine learning, causal machine learning, reinforcement learning, or operations research to clearly defined challenges.

• Produce clear technical documentation.

• Engage in quarterly planning and contribute to roadmap initiatives.

• Adjust as the team's scope broadens into Revenue Cycle Management, Finance, and other areas.

• Report directly to the Director of Data Science and Analytics or a Staff Data Scientist, based on team configuration.

⛳️ Requirements

• Master's degree in a quantitative field (Computer Science, Statistics, Data Science, Operations Research, or a related discipline) is mandatory.

• 4–7 years of experience in data science.

• Previous experience in an early-stage healthcare startup is preferred.

• Practical expertise in claims data and various healthcare data.

• Strong technical background in predictive machine learning, including classification, regression, and forecasting techniques.

• Proficient in Python and SQL; capable of writing, debugging, and optimizing production-quality code.

• Familiarity with the complete software development lifecycle and proficient with GitHub, including version control, branching strategies, pull requests, and code reviews.

• Proven experience in deploying machine learning models into production in collaboration with data engineering.

• Ability to produce clear technical documentation.

• Strong verbal and written communication skills, including the capability to present findings to both technical and non-technical stakeholders.

• Excellent analytical and organizational abilities, managing multiple workstreams and competing priorities.

• Comfortable working in a high-pressure, ambiguous environment where priorities may change.

• Hands-on experience in several of the following domains: reinforcement learning, operations research methods, causal inference, health economics or healthcare claims data, and agentic AI tools or frameworks.

🏝️ Benefits

• Opportunities for professional growth with attractive career pathways.

• Support for a healthy work-life balance through flexible paid time off (PTO).

• Comprehensive benefits package, including medical, dental, vision, short-term disability (STD), and long-term disability (LTD) insurance for full-time employees.

• 401(k) savings plan featuring employer matching contributions.