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
Skills Required
- 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 concepts, including matching, deduplication, entity resolution, golden records, data standardization, data quality, and reference data
- Experience working with large-scale structured and semi-structured datasets
- Experience with Delta Lake or Lakehouse architecture
- Strong understanding of data governance, data quality, and data lineage
- Experience working with healthcare, payer, provider, patient, or other regulated data
- Experience working in a HIPAA-regulated environment
- Experience with healthcare member or patient data and healthcare data models
- Experience with MDM platforms such as Informatica MDM, Reltio, IBM MDM, or similar
- 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 and visualization platforms
- Experience building production-grade machine learning or data science pipelines
- Familiarity with healthcare interoperability standards such as FHIR, HL7, or claims data
v4c.ai Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about v4c.ai and has not been reviewed or approved by v4c.ai.
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Flexible Benefits — Flexible work arrangements, including remote-first and hybrid options, are highlighted across roles and company materials. Flexibility is positioned as part of the benefits package supporting work–life balance.
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Wellbeing & Lifestyle Benefits — Wellbeing offerings such as wellness programs and regular social events are explicitly called out. These lifestyle benefits are framed as supporting employee happiness.
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Healthcare Strength — Comprehensive health insurance plans are stated as part of the package. Health coverage is presented as a core benefit alongside wellness support.
v4c.ai Insights
What We Do
v4c.ai is a premier IT services consultancy specializing in Databricks to help organizations unlock the full potential of their data. We partner with enterprises to accelerate their journey to becoming data-driven by delivering end-to-end Databricks services across Lakehouse implementation, data engineering, AI/ML, and governance. Our expertise in integration, optimization, and enablement empowers clients to unify disparate data sources, modernize analytics, and build AI-ready platforms. By aligning Databricks capabilities with strategic business goals, we help organizations achieve faster insights, stronger competitive advantage, and scalable innovation.
