Data Scientist - Onshore (B)

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