Crunch Numbers. Build Models. Shape Strategy. Create Impact

About LJI
Loyalty Juggernaut (LJI) is a leading B2B SaaS company redefining how enterprises drivecustomer engagement and loyalty. Our flagship platform, GRAVTY®, enables globalbrands to turn loyalty programs into measurable, revenue-generating growth engines.
Built as an AI-first, next-generation solution, GRAVTY® helps organizations deliverpersonalized, real-time experiences at scale, increasing customer lifetime value anddeepening brand relationships. Headquartered in Palo Alto, California, LJI partners withenterprises across 16 major industries, including airlines, retail, hospitality, financialservices and telecommunications.

Our Global Impact:

• 400+ Million members connected through our platform.

• 100+ Global Brands trust us to drive loyalty and brand devotion.

• 3-Time Winner of “Best Technology Innovation in Loyalty”.

• Global recognitions for Excellence in Loyalty Management under numerous categories.

• Recognized as a ‘Robust performer’ in The Forrester Wave™ Loyalty Platforms, Q4 2025.





Explore more about us at www.lji.io.

Role Overview
We are seeking a Data Scientist who can turn statistical ideas into models that loyaltyclients rely on every day. You will build predictive and causal models on member-leveldata from programs with millions of members, run them reliably in production, and explaintheir impact to client stakeholders.

The role is roughly 70% technical (modeling, statistics, engineering of ML systems) and 30% business (framing problems, working with clients, translating results into decisions).You will work closely with Product, Data Engineering, Engineering and Customer Success.

What you will OWN
Predictive & Statistical Modeling (technical):
Design, train and validate models for churn,propensity, next-best-offer, lifetime value, tier migration and anomaly or fraud detection.Choose methods on evidence: regression and GLMs, survival analysis, gradient boosting,probabilistic

📌 Data Scientist (India)
🏢 Loyalty Juggernaut
📍 India