Senior Data Scientist - Customer Loyalty

Role Description

Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. We are seeking a Senior Data Scientist – Causal Inference & Customer Loyalty to join a brand-new Business Unit (BU) supporting leading Retail and CPG clients. In this role, you will:

• Design, develop, and deploy advanced causal and predictive solutions that drive critical business decisions across customer retention, loyalty program optimization, churn mitigation, and lifecycle monetization.
• Work closely with business stakeholders, marketing leaders, data engineers, and analytics leadership to build foundational data models and scalable algorithms that deliver measurable revenue generation from customer behavior.
• Combine strong causal inference expertise with hands-on machine learning experience and the ability to translate complex behavioral data into actionable business recommendations.

Qualifications

• 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 behavioral monetization.
• 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.

Requirements

• 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.

Benefits

• This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.