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# Applied Data Scientist

- **Company:** Wintermeyer Ventures
- **Location:** New York, NY, United States
- **Experience:** Experienced
- **Salary:** $180,000.0 - $240,000.0
- **Contract:** Permanent contract
- **Skills:** Airflow, Amazon Web Services, Amazon S3, Cloud Database, Customer Data Management, Data Integration, Distributed Data Store, Python (Programming Language), PostgreSQL, Software Deployment, SQL Databases, Fast Healthcare Interoperability Resources, Apache Spark, Electronic Medical Records, Pandas, Pyspark, Scikit Learn, Data Analytics, Health Level Seven International, Machine Learning Operations
- **Published:** October 27, 2026
- **Apply:** https://www.careerjet.com/jobad/usddca5fc087d5a74f21f4bc5ab4c0bb2f

## About the Role

* Four or more years of applied data science experience, with strong client-facing skills and the ability to lead working sessions with senior stakeholders.
 * Experience designing and explaining commercially relevant studies, evaluating models honestly, and communicating methodology clearly.
 * Hands-on production Python experience, including pandas, scikit-learn, and Airflow, plus experience shipping code beyond notebooks.
 * Experience building distributed data and machine learning pipelines with Spark or PySpark, and delivering complex systems end to end.
 * Healthcare or life sciences experience, such as work with claims, EHR, HL7/FHIR, lab data, population health analytics, or internal healthcare data.
 * Experience with cloud data and ML tools such as AWS, S3, Glue, EMR, MWAA, SageMaker, SQL, or Postgres is relevant.
 * Must be a US citizen or Green Card holder. Healthcare technology startup experience is a plus.

## Description

Join a healthcare technology team as an Applied Data Scientist, owning customer data science work from study design through production deployment. You will partner with healthcare organizations to turn complex data into practical insights that support better care and business decisions.
What You'll Do

 * Own several enterprise healthcare accounts, from data integration and pilot design through production pipelines and ongoing operations.
 * Design and defend commercially relevant experimental studies, including predictive analyses that help identify patients who may benefit from earlier care.
 * Build automated customer-specific pipelines to train models, generate scores, and deliver insights at scale.
 * Work directly with clinical, analytics, and IT stakeholders to translate business problems into data-driven solutions.
 * Identify patterns across customer engagements and share high-value requirements with product teams.