Job Description

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

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

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growth, marketing, business, category, risk team to bring intelligence in decision making, accuracy in measurement and

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uplift impact on co-owned metrics

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• Influence decisions on the Card's Customer Value Proposition (CVP), and its downstream impact on both customer

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experience and P&L;

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- Drive growth in customer spends and Monthly Active Users as core charter metrics
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- Identify how to convert regular users into "super users," and the levers that drive that transition
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- Define customer segments, optimal interventions, and the journey map to move users up the value ladder
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- Design and run lifecycle-based interventions to induce spend, in partnership with the Cards Business team
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- Build activation, engagement, and retention programs for the Scapia App specifically (not just the card)
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- Build and maintain a view of competitive share of wallet, and how Scapia can grow its share of customer spend
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- Start with goal-specific customer segmentations across LTV initiatives; over time, identify the opportunity to unify these
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into a single, company-wide segmentation that simplifies interventions, tracking, and customer solutions

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- Build and mentor an analytics / data science team as the function scales
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- Use AI tools throughout the workflow — for analysis, modeling, coding, and reporting — to move faster and scale the team's output.
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Example Projects You'll Drive :

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• First-transaction program: get recent customers to their first transaction while minimizing cannibalization of organic

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behavior

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• Power-user conversion program:

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- Define what a "power user" is and identify early indicators that predict who becomes one
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- Design a rewards journey to nudge users toward power-user behaviors (e.g., experiencing a 2% rewards
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transaction, adding a second card, using UPI)

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◦ Minimize cannibalization while designing these incentives

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• Card attrition program:

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- Identify attriters and the early signals that predict attrition
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- Design and run retention interventions to win these users back before they churn
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• Milestone / gamification design:

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- Explore milestone structures beyond a single threshold (e.g., ₹20K for annual percentage/rewards) — monthly vs. annual milestones, tiered targets, etc.
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- Test "fear" (loss-aversion) framing vs. "greed" (reward) framing
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- Competitive wallet-share analysis: understand what else lives in the customer's wallet, and how Scapia can win a larger share.
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- Rewards awareness campaigns: build, run, and measure programs (e.g., "2% everywhere, everyday card") jointly with the Cards Business team
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- App activation modeling: for new/cold-start users (≤45 days), predict which onboarding module or homepage widget
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each customer is most likely to convert on, using onboarding signals, card spend, and travel-affinity predictions etc.

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• App engagement modeling: for repeat users (45+ days), personalize category order, homepage composition, and

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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

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- In-app recommendations: power contextual prompts like "because you searched," "use your coins," or "best fit for your budget" using property-specific signals
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- Next-best-category / next-best-action modeling: drive continued exploration and conversion after a customer's first transaction, based on category-level propensity
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- 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
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What We're Looking For

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• 7–10 years of experience in analytics, data science, or a closely related quantitative field, with demonstrated readiness to

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own a strategic charter rather than execute a defined roadmap. Designs team according to the charter and impact.

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- Track record of driving measurable business outcomes (LTV, retention, activation) — not just reporting
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- Experience designing and analyzing experiments (A/B tests, uplift models) and distinguishing correlation from causal impact
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- Grounded in an analytical approach, with a strong nose for where the real value lies
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- Led by impact and execution, not just analysis for its own sake
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- Has a keen eye for data-led measurement of experiments, with test designs shaped by sample size, bias, and contamination considerations
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- Background in consumer fintech, credit cards, subscription businesses, e-commerce, or another domain where LTV and retention economics are core to the business
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- 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
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- Builds with peers through alignment and collaboration
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- Manages senior stakeholders well, through crisp, impact-led communication
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- Comfort operating with ambiguity in a fast-moving startup environment, and building structure where none exists yet
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- Brings coherence across different projects rather than letting them run as disconnected workstreams
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- Strong SQL skills and hands-on experience with Python/R for building predictive models (churn, LTV, propensity,
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next-best-action)

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

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Nice to Have :

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