Data Scientist

Company Overview:

CashKaro

EarnKaro

BankKaro

Role Summary

We’re hiring a Data Scientist who blends machine learning capability with strong analytical thinking to solve business-critical problems.

This is a 50:50 hybrid role — half your time will go into building and refining ML models (LTV, fraud, targeting, Churn, etc.), and the other half into product analytics, deep-diving funnels, retention, and growth patterns to identify levers for scale.

You’ll work closely with the Head of Data & Analytics and collaborate with Product, CRM, Marketing, and Tech teams to convert ambiguity into models, experiments, and insights that influence ₹1000Cr+ business decisions.

What You'll Work On

1. Applied Data Science (50%)

• Build machine learning models for LTV prediction, fraud detection, churn scoring, etc.
• Do exploratory data analysis, feature engineering, algorithm tuning, and validation
• Translate business goals into modeling problems and take them end-to-end (POC to production-readiness)
• Collaborate with engineering teams to deploy models and track real-world performance
• Automate retraining pipelines, monitoring, or model risk assessment

2. Product & Growth Analytics (50%)

• Deep-dive into funnels, retention curves, feature usage, and cashback behavior
• Identify drop-offs, friction points, and conversion drivers in user journeys
• Analyze campaign/channel performance and recommend optimizations
• Run user segmentation, cohorting, and behavioral clustering
• Design structured frameworks for recurring decision-making

3. Experimentation & Impact Measurement (across both)

• Design and analyze A/B tests, rollouts, or quasi-experiments
• Apply statistical methods (diff-in-diff, uplift modeling, matching) to quantify impact
• Own the measurement framework for product and incentive experiments

Requirements

• 2–3 years of hands-on experience in

  data science or ML-heavy analytics roles

• Proficient in

  Python (pandas, scikit-learn, statsmodels)

  and strong in

  SQL

• Experience building, evaluating, and iterating on ML models using real-world data
• Strong understanding of statistics, experimentation, and causal inference
• Comfortable translating business problems into data science workflows
• Excellent communication — can explain models, assumptions, and trade-offs clearly

Nice-to-Have

• Experience with campaign modeling, churn prediction, fraud detection, or cashback optimization
• Exposure to lifecycle analytics or funnel deep dives
• Familiarity with tools like MLFlow, Airflow, SageMaker, or containerization (Docker)
• Working knowledge of Redshift or AWS stack
• Some experience collaborating closely with product or marketing teams

Tech Stack You’ll Use

• Python

  – pandas, scikit-learn, NumPy, statsmodels, matplotlib/seaborn

• SQL

  – Redshift

• Experimentation

  – internal tools or Python-based frameworks

• Data Infra

  – S3, internal data lake

• Collaboration

  – Git, Slack, Notion, Confluence

Example Projects

• Build a predictive model to forecast LTV at the user onboarding stage
• Detect potential cashback fraud using behavioral clustering and thresholds
• Analyze drop-offs in key business flows and recommend high-leverage product fixes
• Run experiments on CRM campaign personalization and evaluate incremental ROI
• Create a user segmentation framework to power CRM and product targeting

Why This Role?

• Real ML ownership

  : Your models will be used, not just prototyped

• Diverse challenges

  : Switch between modeling, experimentation, and analytics

• High visibility

  : Work closely with founders and senior leaders

• Business impact

  : Influence product, growth, and financial outcomes directly

• Growth-stage momentum

  : Help shape data science as we scale to ₹1000Cr+

This Role is for You If…

• You want to spend 50% of your time building models, but still love structured problem-solving
• You like real-world data, not clean toy datasets
• You enjoy going beyond model accuracy — to understand what it means and why it matters
• You can work independently, but communicate clearly with product, growth, and tech teams

Why Join Us

• Work on real problems

  : Your insights won’t sit in slides — they’ll drive experiments, campaigns, and roadmaps.

• High visibility

  : Work directly with functional leaders and founders.

• Cross-functional exposure

  : Collaborate with marketing, CRM, product, and operations teams.

• Business-first environment

  : We reward impact — not just activity or output.

• Fast-growth company

  : Be part of a rocket ship scaling toward ₹500 Cr+ in revenue.