Senior Data Scientist

Job Summary The Senior Data Scientist will develop advanced customer churn analytics and commercial intelligence solutions using the Microsoft Fabric platform. This hands-on role focuses on predictive analytics, customer retention, propensity modeling, and actionable insights using commercial, provider, and healthcare data. The role will collaborate with data engineering, business intelligence, commercial excellence, sales operations, and enterprise data teams to deliver scalable analytics solutions and measurable business outcomes.

Key Responsibilities Design, develop, and deploy customer churn prediction models within Microsoft Fabric. Build customer health scoring frameworks to identify accounts at risk of reduced adoption or discontinuation. Develop predictive indicators and early warning signals for customer attrition. Create segmentation models to identify retention opportunities and revenue-at-risk accounts. Analyze customer adoption trends, utilization patterns, and engagement behaviors across healthcare provider organizations. Quantify churn drivers and develop actionable recommendations for commercial teams.

Develop end-to-end data science solutions using Microsoft Fabric. Leverage Fabric Notebooks, machine learning capabilities, and Spark environments for model development and deployment. Build scalable feature engineering pipelines supporting predictive analytics use cases. Implement model monitoring and performance measurement processes. Develop reusable analytics assets and data science accelerators within Fabric. Partner with data engineering teams to integrate and curate commercial, provider, claims, customer hierarchy, and master data sources.

Develop customer-level longitudinal datasets that provide a unified view of customer behavior. Engineer predictive features from multiple commercial and healthcare data sources. Utilize Fabric Lakehouse and Data Warehouse architectures to support scalable analytical workloads. Collaborate with data engineers on ETL pipeline design, data modeling, performance optimization, data quality validation, and Lakehouse architecture. Consume and optimize data assets stored in Microsoft Fabric Lakehouse, Microsoft Fabric Data Warehouse, Delta tables, and semantic models.

Ensure analytical solutions align with enterprise architecture and governance standards. Collaborate with Power BI developers to productionize analytical outputs for business users. Design customer churn metrics, KPIs, and analytical datasets for business dashboards. Translate predictive model outputs into actionable business insights and visualization requirements. Participate in Agile ceremonies including sprint planning, daily standups, backlog refinement, sprint reviews, and retrospectives. Deliver incremental business value through rapid prototyping and iterative development.

Contribute to technical documentation, code reviews, and knowledge-sharing activities. Required Qualifications 10+ years of overall professional experience, including 8+ years of experience working in the United States. 7+ years of experience in data science, machine learning, predictive analytics, or commercial analytics. 3+ years of experience in healthcare, life sciences, pharmaceutical, medical device, or related healthcare analytics environments. Hands-on experience with Microsoft Fabric.

Strong experience developing customer churn, propensity, retention, predictive risk, and customer segmentation models. Strong expertise in Python, SQL, PySpark, statistical modeling, and machine learning algorithms. Experience developing data science solutions using Fabric Lakehouse, Data Warehouse, Notebooks, Data Pipelines, or related Microsoft analytics technologies. Experience working with structured and longitudinal customer, commercial, provider, or healthcare datasets. Experience with feature engineering and predictive analytics pipelines.

Experience collaborating with data engineering and business intelligence teams. Experience with Power BI and translating analytical outputs into business insights. Experience working in Agile product delivery environments. Bachelors or Masters degree in Data Science, Statistics, Computer Science, Applied Mathematics, Engineering, or a related quantitative field.

Preferred Qualifications Experience with Microsoft Fabric OneLake and Semantic Models. Experience with Azure DevOps, GitHub, Git-based source control, and CI/CD practices. Experience with DAX and Power BI analytics. Experience working with healthcare claims, provider, commercial, customer, or sales data. Experience developing reusable analytics assets, feature stores, or data science accelerators. Experience with model monitoring and performance measurement. Experience working in fast-paced environments involving rapid prototyping, experimentation, and iterative delivery.

Education: Bachelors Degree