Senior Associate Data Science - CSA

Responsibilities

• Implement and maintain customer analytics models including CLTV prediction, propensity modelling, and churn prediction
• Support the development of customer segmentation models using clustering techniques and behavioural analysis
• Assist in building and maintaining survival models to analyze customer lifecycle events
• Work with large-scale datasets using BigQuery and Snowflake
• Develop and validate machine learning models using Python and cloud-based ML platforms, specifically BQ ML, ModelGarden and Amazon Bedrock
• Help transform model insights into actionable business recommendations
• Collaborate with analytics and activation teams to implement model outputs
• Present analyses to stakeholders in clear, actionable formats
  
  

• Bachelors or master’s degree in Statistics, Mathematics, Computer Science, or related quantitative field
• 2-4 years’ experience in applied data science, preferably in marketing/retail
• Experience in developing and implementing machine learning models
• Strong understanding of statistical concepts and experimental design
• Ability to communicate technical concepts to non-technical audiences
• Familiarity with agile development methodologies
  
  

• SQL and data warehouses (BigQuery, Snowflake)
• Python for statistical modeling
• Machine learning frameworks (scikit-learn, TensorFlow)
• Statistical analysis and hypothesis testing
• Data visualization tools (Matplotlib, Seaborn)
• Version control systems (Git)
• Understanding of Google Cloud Function and Cloud Run
  
  

• Customer lifetime value modeling
• RFM analysis and customer segmentation
• Survival analysis and hazard modeling
• A/B testing and causal inference
• Feature engineering and selection
• Model validation and monitoring
• Cloud computing platforms (GCP/AWS/Azure)
  
  

• Support development and maintenance of CLTV models
• Contribute to customer segmentation models incorporating behavioral and transactional data
• Implement survival models to predict customer churn
• Support the development of attribution models for marketing effectiveness
• Help develop recommendation engines for personalized customer experiences
• Assist in creating automated reporting and monitoring systems
  
  

• Strong analytical and problem-solving abilities
• Good communication and presentation skills
• Business acumen
• Collaborative team player
• Strong organizational skills
• Ability to translate business problems into analytical solutions