Data Scientist (Microsoft Fabric & Customer Analytics)

We are seeking an experienced Data Scientist to develop advanced customer analytics and predictive intelligence solutions within a Microsoft Fabric environment. This role focuses on building machine learning models and analytics products that help organizations identify, understand, and reduce customer attrition while improving engagement, retention, and revenue growth., * Design, develop, and deploy customer churn prediction models using Microsoft Fabric.

• Build customer health scoring models to identify accounts at risk of reduced engagement or discontinuation.
• Develop predictive indicators and early warning systems for customer attrition.
• Create segmentation models to identify retention opportunities and revenue-at-risk customers.
• Analyze customer adoption trends, utilization patterns, and engagement behaviors.
• Identify key churn drivers and provide actionable recommendations to business stakeholders., * Develop and optimize machine learning and statistical models for customer behavior analysis.
• Build predictive analytics solutions using commercial, customer, and operational datasets.
• Perform feature engineering, model validation, and performance monitoring.
• Translate complex analytical findings into business insights and strategic recommendations.

Collaboration & Stakeholder Engagement

• Partner with Data Engineers, BI Developers, Business Analysts, and Commercial Teams.
• Work closely with business stakeholders to understand objectives and define analytical solutions.
• Support the development of dashboards, reporting solutions, and executive-level insights.
• Contribute to continuous improvement of analytics processes and predictive frameworks.

3+ Years of Experience In:

• Data Science
• Machine Learning
• Predictive Analytics
• Commercial Analytics

Proven Experience Developing:

• Customer Churn Models
• Propensity Models
• Retention Analytics
• Predictive Risk Models
• Customer Segmentation Solutions

Strong Expertise In:

• Python
• SQL
• PySpark
• Statistical Modeling
• Machine Learning Algorithms
• Microsoft Fabric
• Microsoft Azure Analytics Ecosystem, * Hands-on experience with Microsoft Fabric, including:
• Lakehouses
• Warehouses
• Notebooks
• Data Pipelines
• Semantic Models
• Power BI
• Strong understanding of customer lifecycle analytics and retention strategies.
• Experience working with large-scale datasets in cloud-based analytics environments.
• Excellent communication and stakeholder management skills., Data Scientist, Machine Learning, Predictive Analytics, Customer Churn, Customer Segmentation, Propensity Modeling, Retention Analytics, Python, SQL, PySpark, Microsoft Fabric, Azure, Statistical Modeling, Power BI, Commercial Analytics, Predictive Modeling, Data Science.