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REQUIREMENT_ID_180 β€’ 3-DAY_ACTIVE_POLICY

Data Analyst

Company
Company JPMorgan Chase
Type
Opportunity Type Internship
Salary
Stipend / Salary β‚Ή6–12 LPA
Location
Location Bangalore
Posted Date
Posted Date Today
SQL Excel Python Data Visualization Tableau PowerBI Statistical Analysis AML/KYC Knowledge Problem Solving Communication
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Placement Papers for Data Analyst Roles Open Resource β†—
Curated set of past placement papers that help candidates practice quantitative and analytical questions relevant to the role.
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Interview Experiences and Tips Open Resource β†—
First‑hand accounts of candidates who cleared the recruitment process, offering insights into question patterns and preparation strategies.
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Comprehensive Interview Preparation Guide Open Resource β†—
A detailed guide covering technical topics, case studies, and soft‑skill preparation for data‑analytics interviews.
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Algorithm Practice Problems Open Resource β†—
A large collection of coding problems to sharpen problem‑solving skills, essential for technical screening rounds.

Graduates (B.Tech/B.E., B.Sc., B.Com, BBA, or equivalent) with a minimum of 60% aggregate (or CGPA 6.5/10). Eligible batch years: 2025, 2026. No active backlogs; maximum of 2 backlogs allowed at the time of application. Preference for candidates from Computer Science, Information Technology, Statistics, Mathematics, Economics, Finance, or related streams. Strong analytical mindset and proficiency in English (both written and verbal) are mandatory.

1
Round 1: Online Aptitude Test (Logical Reasoning, Data Interpretation)
2
Round 2: Technical Interview (SQL, Python, case studies on AML/KYC)
3
Round 3: HR Interview (fitment, motivation, cultural alignment)
J.P. Morgan Chase, a global leader in financial services, has a strong presence in India with a focus on technology, risk management, and client solutions. The firm operates across investment banking, commercial banking, asset management, and treasury services, serving millions of customers worldwide. In India, the company is known for its robust compliance framework, cutting‑edge analytics platforms, and a culture that encourages continuous learning and innovation. Employees benefit from exposure to international best practices, mentorship from seasoned professionals, and opportunities to work on high‑impact projects that shape the global financial ecosystem. The Data Analyst role in the Bangalore office is designed for fresh graduates and early‑career professionals who are eager to translate raw data into actionable insights. As a member of the analytics team, you will collaborate closely with relationship managers, risk officers, and technology partners to ensure data‑driven decision making across client onboarding, AML/KYC compliance, and transaction monitoring. You will be expected to independently investigate anomalies, produce detailed reports, and recommend process improvements that enhance operational efficiency and regulatory adherence. **Key Responsibilities** 1. Address escalated service issues promptly while maintaining high standards of customer satisfaction. 2. Make strategic decisions based on data analysis, insights, and domain experience. 3. Support client onboarding by fulfilling AML and KYC requirements, conducting risk assessments, and documenting compliance evidence. 4. Conduct thorough investigations to identify AML typologies and generate accurate investigative reports. 5. Identify opportunities to refine processes, increase operational efficiencies, and manage stakeholder relationships. 6. Analyze transaction data to detect patterns, verify legitimacy, and flag suspicious activities. 7. Interact with bankers and customers to gather necessary information for investigations. 8. Prepare dashboards and visualizations using tools such as Tableau or Powerβ€―BI to communicate findings to senior leadership. 9. Continuously monitor regulatory updates and incorporate them into analytical frameworks. 10. Contribute to knowledge‑sharing sessions and help build a data‑centric culture within the team. **Tech Stack**: SQL, Python (pandas, numpy), Excel, Tableau/Powerβ€―BI, SAS, AML monitoring platforms, Git for version control. **Growth Path**: Successful analysts can progress to Senior Analyst, Analytics Lead, or specialize in Risk Analytics, Fraud Detection, or Business Intelligence. The firm also offers rotational programs across finance, technology, and compliance, enabling a broad career trajectory. **Why Join J.P. Morgan**: The organization offers a competitive salary range of β‚Ή6–12β€―LPA, world‑class training, exposure to global financial markets, and a collaborative environment that values diversity and inclusion. Freshers receive mentorship, structured learning modules, and the chance to work on real‑world problems that have a direct impact on the bank’s risk posture and client experience.

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 (SQL, Excel, Python, Data Visualization, Tableau, PowerBI, Statistical Analysis, AML/KYC Knowledge, Problem Solving, Communication) & 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 Data Analyst?
Preparation Tip: Highlight JPMorgan Chase's market reputation, recent tech innovations, and how your skills in SQL 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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