Website JPMC
Data Scientist Associate – JPMorgan Chase & Co.
Company: JPMorgan Chase & Co.
Division: International Consumer Bank (ICB) / Chase UK
Team: Business Analytics (Product, Marketing, Operations, & Engineering Squads)
Location: Bengaluru, Karnataka, India
Role Level: Associate (Data Scientist)
Industry: Digital Retail Banking & FinTech
Core Tech Stack: SQL, Python (
pandas, scikit-learn, statsmodels), A/B Testing, Predictive Modeling, Causal InferenceAbout Chase UK & International Consumer Bank
JPMorgan Chase launched Chase UK to transform mobile retail banking through seamless, customer-first digital experiences. Operating with a high-growth startup mindset backed by the global scale of JPMorgan Chase, the International Consumer Bank (ICB) division serves millions of digital banking customers across savings, current accounts, and consumer lending products.
Role Overview
As a Data Scientist Associate within the Business Analytics team, you will embed directly into agile squads alongside Product, Marketing, Operations, and Engineering partners.
Your core focus will be designing and evaluating A/B experiments, mapping customer behavioural journeys, building lightweight predictive models (churn prevention, response propensity, customer lifetime value proxies), and translating complex data into strategic business decisions.
Key Responsibilities
-
Experimentation & A/B Testing: Design, execute, and analyse controlled experiments (A/B tests, multi-arm bandits). Define test guardrails, compute sample sizes/statistical power, and quantify treatment effects with confidence intervals.
-
Predictive Modelling: Construct, evaluate, and maintain interpretable predictive models (logistic/linear regression, decision trees, gradient boosting) for churn risk, propensity scoring, and customer engagement targeting.
-
Customer Journey Analytics: Analyze behavioral funnels, cohort retention, cross-sell adoption, and commercial unit economics to improve customer lifetime value (LTV) and profitability.
-
Data Pipelines & SQL Operations: Write high-performance SQL queries across enterprise data warehouses to extract, aggregate, and validate complex transactional and interaction datasets.
-
Stakeholder Influence: Translate unstructured business questions into testable hypotheses and communicate data-driven recommendations to cross-functional product leads and executive stakeholders.
-
Reproducible Data Science: Maintain best practices for clean documentation, code reviews, metric definitions, and collaboration with Data & Machine Learning Engineering teams.
Required Qualifications & Skillset
-
Technical Skills:
-
Advanced SQL: Complex joins, window functions, query performance optimisation, and data validation.
-
Python for Analytics: Proficient in data science tooling (
pandas,numpy,scikit-learn,statsmodels) for reproducible scripting. -
Statistics & Experimentation: Strong foundation in hypothesis testing, sample size estimation, variance reduction, and bias/confounding mitigation.
-
-
Domain Experience: Proven track record in customer analytics (funnel conversion, cohort dynamics, marketing campaign attribution) and commercial unit economics.
-
Communication: Exceptional ability to craft compelling data narratives for both technical and business audiences.
Preferred Qualifications
-
Causal Inference & Quasi-Experiments: Familiarity with Difference-in-Differences (Diff-in-Diff), propensity score matching (PSM), and synthetic controls when randomized testing is unfeasible.
-
Model Governance & Monitoring: Understanding of feature leakage prevention, probability calibration, population stability index (PSI), and model drift monitoring.
Role Summary
| Attribute | Details |
| Job Title | Data Scientist Associate |
| Company | JPMorgan Chase & Co. |
| Business Unit | International Consumer Bank (Chase UK) |
| Location | Bengaluru, Karnataka, India |
| Focus Areas | A/B Testing, Behavioral Analytics, Churn & Propensity Modeling |
| Core Stack | SQL, Python, Statistics, A/B Testing, Causal Inference, Scikit-Learn |
Follow Us