Data Scientist
Job Description
Key Skills Required
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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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v4c.ai
View Company Profilev4c.ai is an IT services consultancy and systems integrator specializing in enterprise data modernization, cloud data platforms, and artificial intelligence solutions. Founded in 2024 and headquartered in Scottsdale, Arizona, the firm delivers end-to-end solutions centered on Databricks Lakehouse architecture and Dataiku, offering expertise across data engineering, MLOps, and generative AI deployment.
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