[Remote] Senior Data Scientist - Customer Loyalty

Note: The job is a remote job and is open to candidates in USA. Tiger Analytics is looking for experienced Data Scientists to join their advanced analytics consulting firm. The Senior Data Scientist will design, develop, and deploy advanced causal and predictive solutions to drive business decisions across customer retention and loyalty programs.

Responsibilities

• Design, develop, and deploy causal inference models (e.g., uplift modeling, synthetic control, double machine learning) to understand the true drivers of customer loyalty and measure the incremental impact of marketing interventions
• Build robust machine-learning-based forecasting and predictive models for customer lifetime evaluation (LTV) and customer churn
• Establish foundational data modeling frameworks for a brand-new Business Unit, transforming raw transactional data into scalable features
• Analyze complex customer behavior, purchase patterns, and engagement metrics to build strategies for direct revenue generation
• Perform large-scale data extraction, transformation, and analysis using SQL
• Partner with marketing, product, and business teams to understand loyalty requirements and translate business problems into analytical solutions
• Present model insights and recommendations to senior client stakeholders, clearly communicating the difference between correlation and causation
• Lead workshops and customer analytics strategy discussions with clients
• Implement and operationalize models in cloud environments

Skills

• 6+ years of experience in applied data science or advanced analytics
• 4+ years of hands-on experience in customer analytics, customer loyalty programs, churn prediction, or behavioural monetisation
• Strong domain experience in CPG, FMCG, retail, or similar consumer-facing industries
• Advanced proficiency in Python (pandas, NumPy, scikit-learn) and causal inference libraries (e.g., EconML, DoWhy, CausalML)
• Strong SQL skills for large-scale data processing and complex data modeling
• Demonstrated experience in building data models and analytics capabilities from the ground up for new business units or initiatives

Company Overview

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