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Tiger Analytics

Senior Data Scientist – Customer Loyalty

Tiger Analytics

Senior Data Scientist at Tiger Analytics focusing on customer loyalty and causal inference. Designing and deploying advanced models for business-critical decisions in retail and CPG sectors.

Posted 6/16/2026full-timeRemote • 🇺🇸 United StatesSeniorWebsite

Tech Stack

Tools & technologies
CloudNumpyPandasPythonScikit-LearnSQL

About the role

Key responsibilities & impact
  • 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.

Requirements

What you’ll need
  • 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.

Benefits

Comp & perks
  • 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.

ATS Keywords

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Hard Skills & Tools
causal inference modelsuplift modelingsynthetic controldouble machine learningmachine learningforecasting modelspredictive modelsdata modeling frameworksSQLPython
Soft Skills
communicationleadershipanalytical thinkingcollaborationpresentation skills