- Location: Bangalore
- Experience: 7–10 years in analytics / data science
- Mandate: Own and grow Customer Lifetime Value across the Scapia Card and App

Scope of the Role

- Own the LTV charter for Scapia customers: activation, engagement, retention, and monetization. Partner with product,

growth, marketing, business, category, risk team to bring intelligence in decision making, accuracy in measurement and uplift impact on co-owned metrics
- Influence decisions on the Card's Customer Value Proposition (CVP), and its downstream impact on both customer experience and P&L;
- Drive growth in customer spends and Monthly Active Users as core charter metrics
- Identify how to convert regular users into "super users," and the levers that drive that transition
- Define customer segments, optimal interventions, and the journey map to move users up the value ladder
- Design and run lifecycle-based interventions to induce spend, in partnership with the Cards Business team
- Build activation, engagement, and retention programs for the Scapia App specifically (not just the card)
- Build and maintain a view of competitive share of wallet, and how Scapia can grow its share of customer spend
- Start with goal-specific customer segmentations across LTV initiatives; over time, identify the opportunity to unify these into a single, company-wide segmentation that simplifies interventions, tracking, and customer solutions
- Build and mentor an analytics / data science team as the function scales
- Use AI tools throughout the workflow — for analysis, modeling, coding, and reporting — to move faster and scale the team's output.

Example Projects You'll Drive :

- First-transaction program: get new customers to their first transaction while minimizing cannibalization of organic behavior
- Power-user conversion program:

◦ Define what a "power user" is and identify early indicators that predict who becomes one

◦ Design a rewards journey to nudge users toward power-user behaviors (e.g., experiencing a 2% rewards transaction, adding a second card, using UPI)

◦ Minimize cannibalization while designing these incentives

- Card attrition program:





◦ Identify attriters and the early signals that predict attrition

◦ Design and run retention interventions to win these users back before they churn

- Milestone / gamification design:

◦ Explore milestone structures beyond a single threshold (e.g., ₹20K for annual percentage/rewards) — monthly vs. annual milestones, tiered targets, etc.

◦ Test "fear" (loss-aversion) framing vs. "greed" (reward) framing

- Competitive wallet-share analysis: understand what else lives in the customer's wallet, and how Scapia can win a larger share.
- Rewards awareness campaigns: build, run, and measure programs (e.g., "2% everywhere, everyday card") jointly with the Cards Business team
- App activation modeling: for new/cold-start users (≤45 days), predict which onboarding module or homepage widget each customer is most likely to convert on, using onboarding signals, card spend, and travel-affinity predictions etc.
- App engagement modeling: for repeat users (45+ days), personalize category order, homepage composition, and widget/collection ranking using lifecycle signals (last click, last purchase, last travel), intent, and session-level history — including building a real-time category affinity score per customer
- In-app recommendations: power contextual prompts like "because you searched," "use your coins," or "best fit for your budget" using property-specific signals
- Next-best-category / next-best-action modeling: drive continued exploration and conversion after a customer's first transaction, based on category-level propensity
- App churn and retention modeling: shift focus from growth to retention as usage signals decline, using inactivity and usage-pattern data to predict churn propensity

What We're Looking For





- 7–10 years of experience in analytics, data science, or a closely related quantitative field, with demonstrated readiness to own a strategic charter rather than execute a defined roadmap. Designs team according to the charter and impact.
- Track record of driving measurable business outcomes (LTV, retention, activation) — not just reporting
- Experience designing and analyzing experiments (A/B tests, uplift models) and distinguishing correlation from causal impact

◦ Grounded in an analytical approach, with a strong nose for where the real value lies

◦ Led by impact and execution, not just analysis for its own sake

◦ Has a keen eye for data-led measurement of experiments, with test designs shaped by sample size, bias, and contamination considerations

- Background in consumer fintech, credit cards, subscription businesses, e-commerce, or another domain where LTV and retention economics are core to the business
- Experience partnering directly with Product, Growth, Marketing, Risk, and Business teams to embed data science into the roadmap — and influencing decisions at the leadership level
- Builds with peers through alignment and collaboration
- Manages senior stakeholders well, through crisp, impact-led communication
- Comfort operating with ambiguity in a fast-moving startup environment, and building structure where none exists yet
- Brings coherence across different projects rather than letting them run as disconnected workstreams
- Solid SQL skills and hands-on experience with Python/R for building predictive models (churn, LTV, propensity,

next-best-action)
- Fluency with AI tools (e.g., coding copilots, LLM-based analysis/automation) as part of everyday working style, not just as a side skill.

Nice to Have :

- Prior experience leading or mentoring analytics/data science teams, including building a function or team from scratch
- Familiarity with modern data stacks (dbt, Airflow, Snowflake/BigQuery/Redshift, or similar)
- Experience with experimentation/feature-flagging platforms
- Exposure to rewards/loyalty program design or gamification mechanics

📌 Analytics and Data Science Lead (Bengaluru)
🏢 Scapia
📍 Bengaluru