Staff Data Scientist (Remote) — Healthcare ML & Impact

MedBridge Inc.; Clayton (NC); Remote; USD 140,000 - 190,000; Full time

Job summary

Medbridge is seeking a Staff Data Scientist to lead end-to-end predictive modeling initiatives across acute, post-acute, and ambulatory care. You will partner with product, engineering, clinical, and customer teams to frame problems, select methods, build and validate models, and deploy them to production in Snowflake with data engineering support.

You will own model development from data to production, monitor performance, retrain as needed, and ensure trustworthy, ethical use of healthcare

Qualifications

• Degree in statistics, biostatistics, computer science, economics, or equivalent quantitative discipline.
• Experience with patient-reported outcomes, risk adjustment, or outcomes benchmarking in provider/payer/quality settings.
• Experience with EHR/EMR or claims data.
• Experience building recommendation systems and measuring adoption and impact.
• Ability to ship models from concept to production with product/engineering partners.

Responsibilities

• Own the design, development, validation, and production operation of predictive and risk-adjustment models.
• Frame problems with product and clinical partners; choose methods and monitor performance.
• Write production-quality, tested code; deploy and monitor in Snowflake with Data Engineering.
• Evaluate impact on patient outcomes and ensure ethical use of healthcare data.

Skills

Python

SQL

Causal inference

Experimentation

Communication

Education

Degree in statistics/biostatistics/computer science/economics

Tools

Snowflake

Version control

Job description

Medbridge is seeking a Staff Data Scientist to lead end-to-end predictive modeling initiatives across acute, post-acute, and ambulatory care. You will partner with product, engineering, clinical, and customer teams to frame problems, select methods, build and validate models, and deploy them to production in Snowflake with data engineering support.

You will own model development from data to production, monitor performance, retrain as needed, and ensure trustworthy, ethical use of healthcare