Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.
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.
You will 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. The ideal candidate combines strong causal inference expertise with hands-on machine learning experience and the ability to translate complex behavioral data into actionable business recommendations.
Key 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.
Requirements
- 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
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.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
Skills Required
- 6+ years of experience in applied data science or advanced analytics.
- 4+ years of hands-on experience in customer analytics, loyalty programs, churn prediction, or behavioral monetization.
- Domain experience in CPG, FMCG, retail, or similar consumer-facing industries.
- Advanced proficiency in Python (pandas, NumPy, scikit-learn).
- Experience with causal inference libraries (EconML, DoWhy, CausalML) and causal methods (uplift modelling, synthetic control, double machine learning).
- Strong SQL skills for large-scale data processing and complex data modeling.
- Demonstrated experience building data models and analytics capabilities from the ground up for new business units or initiatives.
- Experience implementing and operationalizing models in cloud environments.
- Ability to communicate model insights to senior stakeholders and lead client workshops/strategy discussions.
Tiger Analytics Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Tiger Analytics and has not been reviewed or approved by Tiger Analytics.
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Fair & Transparent Compensation — Feedback suggests pay is viewed as fair and market-aligned for many roles and geographies. Consistent, on-time pay and competitive packages in key markets reinforce a generally positive baseline.
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Healthcare Strength — Feedback suggests U.S. medical coverage is strong, with administration via a known benefits platform and plan options seen positively. Health insurance is often regarded as a bright spot within the package.
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Leave & Time Off Breadth — Feedback suggests generous PTO, paid sick days and holidays, and flexible PTO alongside remote-work options. These elements indicate broad time-off provisions available on paper.
Tiger Analytics Insights
What We Do
Tiger Analytics is a global leader in AI and Analytics, helping Fortune 1000 companies solve their toughest challenges. We offer fullstack AI and analytics services & solutions to empower businesses to achieve real outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty and move forward decisively. Our purpose is to provide certainty to shape a better tomorrow. Our team of 4000+ technologists and consultants are based in the US, Canada, the UK, India, Singapore, and Australia, working closely with clients across CPG, Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. We are Great Place to Work-Certified™ and have been recognized by analyst firms such as Forrester, Gartner, Everest, ISG, HFS, and others. Ranked among the ‘Best’ and ‘Fastest Growing’ analytics firms lists by Inc., Financial Times, Economic Times and Analytics India Magazine. In India, our offices are located in Chennai, Hyderabad and Bangalore.









