[Remote] Staff Data Scientist | Individual Contributor | Data & Machine Learning

Note: The job is a remote job and is open to candidates in USA. Medbridge is a software as a service company developing technology solutions for healthcare providers to help patients improve outcomes while reducing the cost of care. The Staff Data Scientist will lead the design, validation, deployment, monitoring, and evaluation of predictive, statistical, and risk-adjustment models, while establishing data science standards and practices through cross-functional influence.

Responsibilities

• Own the design, development, validation, and production operation of Medbridge's predictive and risk-adjustment models, beginning with the models behind our outcomes benchmarking product
• Set the methodological bar: choose approaches that fit the question and the data, validate to a standard that holds up to outside expert scrutiny, and document decisions so partners understand and can question them
• Write production-quality code: tested, versioned, reviewed, and reproducible, and own its deployment and monitoring in Snowflake in partnership with Data Engineering
• Estimate whether Medbridge products, programs, and content change patient outcomes, using experimental and observational methods, and shape the instrumentation that makes those estimates possible
• Turn ambiguous goals into well-posed problems with options and tradeoffs, work directly with product, engineering, clinical, and customer-facing teams to get models into the product, and establish the team's practices for evaluation, documentation, monitoring, and responsible use of healthcare data

Skills

• A track record of models that ran in production and held up: you have owned model code through deployment, monitoring, and retraining, and you can describe what broke and how you fixed it
• Statistical depth you use every day: you reason about how the data were generated, recognize when a model's assumptions fail, quantify uncertainty, and can explain why one method fits a problem and another does not
• Strong Python and SQL and disciplined software engineering, including testing, version control, code review, and reproducible pipelines
• Experience with messy real-world healthcare data, including product data used by clinicians, administrators, or patients, and working knowledge of causal inference and evaluation design
• Experience taking a model from an open-ended business goal to a shipped product feature in partnership with product and engineering, and comfort being the first person on a problem
• Judgement under constraint: when the data, timeline, or requirements are not what the ideal method assumes, you find a path to a defensible solution, explain the tradeoffs plainly, and know what would let you strengthen it later
• Clear communication with clinical, product, and leadership audiences, including plain explanations of uncertainty, limitations, and tradeoffs, and a commitment to trustworthy, ethical use of healthcare data
• Curiosity about new methods and tools, paired with the judgment to evaluate them before adopting them
• A degree in statistics, biostatistics, computer science, economics, or another quantitative discipline, or equivalent capability developed through another professional path. We welcome nonlinear backgrounds and evaluate demonstrated scope and impact rather than relying on a specific credential or number of years
• Snowflake experience is strongly preferred
• Experience with patient-reported outcome measures, risk adjustment, or outcomes benchmarking in a provider, payer, or quality-reporting setting
• Experience with electronic health record (EHR), electronic medical record (EMR), or claims data
• Experience building recommendation systems and measuring their adoption and downstream impact
• Experience evaluating generative AI applications in a regulated domain (such as healthcare), including efficacy and safety review
• Model documentation and validation that has withstood external review, such as diligence, audit, regulatory submission, or peer review
• Experience as the first data science or ML hire in an organization

Benefits

• We are a remote first company
• We hire them and help them grow

Company Overview

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