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Open nowPosted 16 days ago

Data Scientist - Onshore (B)

Workable (global search)107,990 open roles

Where
United States
Work mode
Remote
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Your applicationOpen nowData Scientist - Onshore (B)Workable (global search) · United States

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Early applications get read.

7.9% of postings close within 7 days. Measured by our own scanner across the market. Workable (global search) postings stay open a median of 6 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
  3. 7.9%7 days
  4. 14.9%14 days
  5. 34.0%30 days
This job: posted 16 days ago

Workable (global search) median: 6 days open

The posting

V4C is seeking a Data Scientist with strong experience in Databricks, Python, machine learning, and Master Data Management (MDM) to help build data-driven solutions that support healthcare and member engagement initiatives. The ideal candidate will have experience working with large, complex healthcare datasets and transforming disparate data sources into reliable, analytics-ready data.

Key Responsibilities

  • Develop and productionize machine learning models, statistical analyses, and predictive analytics using Python and Databricks.
  • Build and maintain scalable data science workflows using Databricks, PySpark, SQL, Delta Lake, and related cloud data technologies.
  • Work with MDM processes and frameworks to establish consistent, accurate, and trusted master data across multiple source systems.
  • Analyze and resolve data quality, duplication, matching, and entity-resolution issues across member, provider, patient, and other healthcare-related datasets.
  • Partner with Data Engineering, Product, Analytics, and business stakeholders to translate healthcare business problems into data science solutions.
  • Develop data validation, profiling, and quality-monitoring approaches to improve reliability of analytical datasets.
  • Perform exploratory data analysis and identify trends, patterns, and insights that can support member engagement and healthcare outcomes.
  • Contribute to feature engineering, model evaluation, experimentation, and deployment of data science solutions into production.
  • Ensure data solutions follow applicable healthcare data privacy, security, and governance requirements, including HIPAA where applicable.
  • Document models, datasets, assumptions, methodologies, and data lineage to support reproducibility and governance.

Required Qualifications

  • 8+ years of experience in Data Science, Machine Learning, Advanced Analytics, or a related field.
  • Strong hands-on experience with Databricks and PySpark.
  • Advanced Python and SQL skills.
  • Experience developing and deploying machine learning or predictive models.
  • Strong understanding of Master Data Management (MDM) concepts, including:
  • Data matching and deduplication
  • Entity resolution
  • Golden/master records
  • Data standardization
  • Data quality
  • Reference/master data
  • Experience working with large-scale structured and semi-structured datasets.
  • Experience with Delta Lake / Lakehouse architecture.
  • Strong understanding of data governance, data quality, and data lineage.
  • Experience working with healthcare, payer, provider, patient, or other regulated data is preferred.
  • Experience working in a HIPAA-regulated environment is highly desirable.

Preferred Qualifications

  • Experience with healthcare member/patient data and healthcare data models.
  • Experience with MDM platforms such as Informatica MDM, Reltio, IBM MDM, or similar technologies.
  • Experience with cloud platforms such as Azure or AWS.
  • Experience with MLflow or similar model lifecycle management tools.
  • Experience with Power BI, Tableau, or other analytics/visualization platforms.
  • Experience building production-grade ML/data science pipelines.
  • Familiarity with healthcare interoperability standards such as FHIR, HL7, or claims data is a plus.

Core Skills Data Science: Python, Machine Learning, Statistics, Predictive Analytics Databricks: Databricks, PySpark, Delta Lake, MLflow Data: SQL, Data Quality, Data Governance, Data Lineage, Data Modeling MDM: Master Data Management, Entity Resolution, Matching, Deduplication, Golden Records Healthcare: Healthcare Data, HIPAA, Patient/Member Data, FHIR/HL7 Cloud: Azure/AWS

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