Senior Data Scientist — Production ML for Healthcare

MedBridge

Bellevue (WA)

A distancia

USD 190.000 - 220.000

Jornada completa

14 días+

Una candidatura completa en un minuto

Currículum y carta de presentación personalizados, listos para enviar.

Supera los filtros ATS

Descripción de la vacante

Medbridge is seeking a Staff Data Scientist to lead predictive and statistical models that enable fair comparison of patient outcomes across providers. You will own the model lifecycle from framing with product partners to deployment in Snowflake, with monitoring and retraining as needed.

You will collaborate with product, engineering, and clinical teams to estimate impact and ensure trustworthy use of healthcare data, while adhering to strong ethics and governance.

Formación

  • Track record of models in production and spent time deploying, monitoring and retraining.
  • Strong statistical depth with uncertainty quantification and analysis.
  • Experience with messy real-world healthcare data and clinician-facing products.

Responsabilidades

  • Own design, validation and production operation of predictive models in Snowflake.
  • Set methodological standards, justify approaches and document decisions.
  • Write production-quality code with tests, version control and reproducible pipelines.
  • Estimate impact of products and content on patient outcomes using proper design.
  • Collaborate with product, engineering, clinical and customer teams to ship models.

Conocimientos

Python
SQL
Production code
Statistical modeling
Causal inference
Healthcare data
Experiment design

Educación

Statistics or CS degree

Herramientas

Snowflake

Descripción del empleo

Medbridge is seeking a Staff Data Scientist to lead predictive and statistical models that enable fair comparison of patient outcomes across providers. You will own the model lifecycle from framing with product partners to deployment in Snowflake, with monitoring and retraining as needed.

You will collaborate with product, engineering, and clinical teams to estimate impact and ensure trustworthy use of healthcare data, while adhering to strong ethics and governance.

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