Customer Analytics Scientist

Job Summary

We are seeking a highly motivated Customer Analytics Scientist to join our growing Data Science team. The ideal candidate will leverage advanced analytics, machine learning, and statistical techniques to understand customer behavior, improve customer experiences, and drive business growth. This role will partner closely with marketing, product, sales, and leadership teams to transform customer data into actionable insights and strategic recommendations.

Key Responsibilities

Customer Behavior Analysis

• Analyze customer journeys, purchasing patterns, and engagement metrics.
• Identify customer segments and behavioral trends using data-driven techniques.
• Develop customer lifetime value (CLV) models and retention strategies.

Predictive Modeling

• Build predictive models for customer acquisition, churn prediction, and upsell opportunities.
• Develop recommendation engines and personalization algorithms.
• Create forecasting models to improve customer engagement and revenue generation.

Experimentation & Optimization

• Design and execute A/B tests and experiments to evaluate marketing campaigns and product features.
• Measure campaign effectiveness and identify opportunities for optimization.
• Monitor model performance and continuously improve predictive accuracy.

Data Visualization & Reporting

• Create dashboards and interactive reports using business intelligence tools.
• Present findings and recommendations to technical and non-technical stakeholders.
• Translate complex analytical insights into business actions.

Cross-Functional Collaboration

• Partner with marketing, product, sales, and engineering teams to solve customer-related business problems.
• Support strategic initiatives by providing analytical recommendations and customer insights.
• Contribute to data-driven decision-making across the organization.

Data Management & Governance

• Ensure data quality, consistency, and integrity across customer data sources.
• Implement best practices for data privacy and security compliance.
• Document methodologies, models, and analytical processes.

Required Qualifications

• Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related field.
• 3–6+ years of experience in customer analytics, data science, or business analytics.
• Strong proficiency in Python, SQL, and statistical analysis.
• Experience with machine learning techniques such as classification, clustering, regression, and recommendation systems.
• Hands-on experience with Power BI, Tableau, or Looker.
• Excellent communication and stakeholder management skills.

Preferred Qualifications

• Master’s degree in Data Science, Analytics, Statistics, or a related field.
• Experience with cloud platforms (AWS, Azure, or GCP).
• Knowledge of marketing analytics, CRM systems, and customer segmentation methodologies.
• Familiarity with big data technologies such as Spark or Databricks.

Technical Skills

• Programming: Python, SQL, R
• Machine Learning: Scikit-learn, XGBoost, TensorFlow
• Data Visualization: Power BI, Tableau, Looker
• Databases: SQL Server, PostgreSQL, Snowflake
• Cloud Platforms: AWS, Azure, Google Cloud Platform
• Analytics Techniques: Customer Segmentation, Churn Prediction, Customer Lifetime Value (CLV), Recommendation Systems, A/B Testing

Key Performance Indicators (KPIs)

• Customer Retention Rate
• Customer Lifetime Value (CLV)
• Churn Prediction Accuracy
• Campaign Conversion Rate
• Revenue Growth from Personalization Initiatives
• Customer Engagement Metrics
• Recommendation Model Performance