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REQUIREMENT_ID_1468 β€’ 3-DAY_ACTIVE_POLICY

Client Data Analyst

Company
Company JPMorgan Chase
Type
Opportunity Type Internship
Salary
Stipend / Salary 6 LPA - 8 LPA
Location
Location Bengaluru, Karnataka
Posted Date
Posted Date Yesterday
Data analysis KYC/AML knowledge Microsoft Excel PowerPoint Word Digital literacy Problem solving Stakeholder management Communication Process improvement Attention to detail
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Placement Papers for Analyst Roles Open Resource β†—
Provides previous year papers and solutions to help candidates practice the type of questions asked in analyst recruitment processes.
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Interview Experiences and Tips for Analyst Positions Open Resource β†—
Shares real candidate experiences, interview rounds and preparation strategies specific to analyst roles.
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Comprehensive Preparation Guides Open Resource β†—
Offers curated study plans, topic‑wise notes and mock tests useful for aptitude and technical rounds.
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Algorithm Practice Problems Open Resource β†—
A collection of coding and problem‑solving questions to sharpen logical reasoning and data‑manipulation skills.

Graduates (B.Tech/B.E., B.Com, BBA, BA) with a minimum of 60% aggregate (or CGPA 6.0/10). Preferred streams: Finance, Economics, Business Administration, Computer Science or Engineering. Freshers from the 2025 or 2026 batch are encouraged to apply. No active backlogs at the time of joining. Strong communication skills in English required.

1
Round 1: Online assessment (aptitude & logical reasoning)
2
Round 2: Technical interview (data handling, KYC/AML concepts, case studies)
3
Round 3: HR interview (fitment, motivation, cultural alignment)
J.P. Morgan Chase, a pillar of the global financial services industry for over two centuries, operates across investment banking, consumer banking, commercial banking, asset management and more. In India, the firm is known for its strong culture of meritocracy, continuous learning and a commitment to diversity and inclusion. The Asset & Wealth Management division helps high‑net‑worth individuals and institutions grow and protect their wealth through sophisticated investment strategies and personalized advisory services. Working at J.P. Morgan means being part of a collaborative ecosystem where technology, data and regulatory expertise converge to deliver world‑class solutions. The role of Client Data Analyst in Operations sits at the intersection of data quality, regulatory compliance and client experience. You will be responsible for reviewing, validating and enriching KYC (Know Your Customer) and AML (Anti‑Money‑Laundering) data, ensuring that every client record meets the stringent standards set by regulators and internal risk teams. By leveraging digital tools such as advanced Excel functions, workflow automation platforms and data‑visualisation software, you will streamline onboarding processes, reduce manual effort and improve turnaround times. The position offers exposure to senior bankers, risk officers and technology partners, making it an ideal launchpad for a career in financial operations, risk management or data analytics. Key Responsibilities: 1. Address escalated service issues promptly while maintaining high customer‑service standards. 2. Independently make strategic decisions based on data insights and operational experience. 3. Support client onboarding by fulfilling AML and KYC requirements and conducting risk assessments. 4. Conduct deep‑dive investigations to identify AML typologies and produce accurate investigative reports. 5. Identify and implement process‑improvement opportunities to boost operational efficiency. 6. Analyse transaction data to detect patterns, verify legitimacy and liaise with bankers and customers for additional information. 7. Maintain stakeholder relationships across compliance, technology and front‑office teams. 8. Prepare and present regular metrics on data quality, turnaround time and compliance adherence. 9. Contribute to thought‑leadership initiatives, sharing best practices and fostering a culture of accountability. 10. Participate in digital automation projects to reduce manual touchpoints. Tech Stack & Tools: Microsoft Excel (advanced formulas, Power Query), PowerPoint, Word, data‑visualisation tools (Tableau/Power BI), workflow automation platforms (UiPath, Blue Prism), mainframe and PC‑based banking systems. Growth Path: Successful analysts can progress to Senior Analyst, Team Lead, and eventually to Manager – Risk Operations or Data Governance roles. The exposure to regulatory frameworks and digital transformation projects equips candidates for future roles in compliance, risk analytics or product management. Why Join J.P. Morgan? The firm offers a structured learning environment, mentorship from industry veterans, and a clear career ladder. Employees enjoy competitive compensation, robust benefits, and the chance to work on high‑impact projects that shape the future of global finance. The inclusive culture encourages innovation, continuous upskilling and a healthy work‑life balance.

JPMorgan Chase β€” Data Analytics & SQL Interview Guide

Previously asked questions, exam syllabus, coding benchmarks & round strategy.

APTITUDE & LOGIC πŸ“–
Aptitude Practice Questions & Online Mock Tests

Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.

Open Resource β†—
COMPANY GUIDE 🎯
JPMorgan Chase Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for JPMorgan Chase and off-campus tech roles.

Open Resource β†—
MOCK TESTS & PAPERS πŸ“
Comprehensive Interview Prep Resources & Syllabus

Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.

Open Resource β†—
CODING PRACTICE πŸ’»
Algorithm and Data Structure Problem Set

Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.

Open Resource β†—
Round 1: Online Assessment (OA)
Aptitude, Quantitative Logic & 2 Coding Problems
Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1
Core Tech Stack (Data analysis, KYC/AML knowledge, Microsoft Excel, PowerPoint, Word, Digital literacy, Problem solving, Stakeholder management, Communication, Process improvement, Attention to detail) & Live Code Tracing
Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving
Database Schemas, APIs & Architecture Basics
Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion
JPMorgan Chase Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
What is the difference between WHERE and HAVING clauses in SQL? Answer β–Ό
Model Answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer β–Ό
Model Answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer β–Ό
Model Answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer β–Ό
Model Answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer β–Ό
Model Answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
Why do you want to join JPMorgan Chase as a Client Data Analyst?
Preparation Tip: Highlight JPMorgan Chase's market reputation, recent tech innovations, and how your skills in Data analysis directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Preparation Tip: Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Preparation Tip: Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.

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