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REQUIREMENT_ID_82 β€’ 3-DAY_ACTIVE_POLICY

Associate Data Analyst

Company
Company MetLife
Type
Opportunity Type Internship
Salary
Stipend / Salary 4.5 LPA
Location
Location Pune, Maharashtra
Posted Date
Posted Date Yesterday
Excel SQL Data Visualization Analytical Thinking Problem Solving Communication
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Aptitude and Reasoning Practice Set Open Resource β†—
Covers quantitative, logical, and data interpretation questions to help you ace the online assessment for the analyst role.
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MetLife Recruitment Process Insights Open Resource β†—
Provides first‑hand experiences of candidates who cleared MetLife's interview rounds, useful for preparation strategy.
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Data Analyst Interview Guide for MetLife Open Resource β†—
Curated list of topics, sample questions, and tips specifically aimed at the Associate Data Analyst position.
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Algorithm and Data Structure Problem Set Open Resource β†—
Practice platform for coding and problem‑solving skills that may be tested in technical rounds.

Bachelor's degree in Computer Science, Information Technology, Statistics, Mathematics, Economics, Business Administration or any related discipline. Minimum 60% aggregate (or CGPA 6.0/10). No active backlogs; maximum of 2 backlogs allowed at the time of application, all must be cleared before joining. Candidates from the 2025, 2026 or 2027 graduating batches are eligible.

1
Round 1: Online Aptitude Test (Logical Reasoning, Data Interpretation, SQL basics)
2
Round 2: Technical Interview (SQL queries, Excel case studies, data visualization concepts)
3
Round 3: HR Interview (fitment, communication, career aspirations)
MetLife, a global leader in insurance, employee benefits, and financial services, has a strong presence in India with offices in major metros including Pune, Bengaluru, and Gurgaon. The company prides itself on a customer‑centric culture, leveraging data and technology to design innovative solutions that protect lives and assets. With a workforce of over 30,000 professionals worldwide, MetLife encourages a collaborative environment where fresh talent can learn from seasoned experts, benefit from structured training programs, and contribute to high‑impact projects that shape the future of insurance analytics. The role of Associate Data Analyst in Pune is designed for recent graduates who are eager to translate raw data into actionable business insights. As an entry‑level analyst, you will work closely with cross‑functional business teams, product managers, and senior data scientists to understand data requirements, build dashboards, and support decision‑making processes. This position offers a solid foundation in data analytics, exposure to real‑world business problems, and a clear career trajectory toward senior analyst or data scientist roles within MetLife’s analytics hub. Key Responsibilities: 1. Collect, clean, and validate large data sets from internal and external sources. 2. Perform exploratory data analysis to uncover trends, patterns, and anomalies. 3. Develop and maintain interactive dashboards and visual reports using tools such as Power BI or Tableau. 4. Translate business questions into analytical queries and deliver concise findings. 5. Collaborate with business stakeholders to define data requirements and ensure alignment with strategic goals. 6. Document data pipelines, methodologies, and reporting standards for reproducibility. 7. Monitor data quality metrics and implement corrective actions when discrepancies arise. 8. Support ad‑hoc analytical projects and contribute to continuous improvement initiatives. 9. Participate in knowledge‑sharing sessions and stay updated with emerging analytics techniques. 10. Assist senior analysts in building predictive models and statistical analyses where required. Tech Stack: Excel, SQL, Power BI/Tableau, basic Python/R for data manipulation, and familiarity with data warehousing concepts. Growth Path: Starting as an Associate Data Analyst, high performers can progress to Data Analyst, Senior Data Analyst, and eventually to Analytics Lead or Data Scientist roles, with opportunities to specialize in areas like risk analytics, customer insights, or product analytics. Why Join MetLife? The company offers a structured onboarding program, mentorship from industry veterans, competitive compensation, and a culture that values continuous learning. Employees enjoy flexible work arrangements, a focus on work‑life balance, and access to global best practices in insurance analytics, making it an ideal launchpad for a data‑driven career.

MetLife 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 🎯
MetLife Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for MetLife 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 (Excel, SQL, Data Visualization, Analytical Thinking, 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
MetLife 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 MetLife as a Associate Data Analyst?
Preparation Tip: Highlight MetLife's market reputation, recent tech innovations, and how your skills in Excel 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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