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JD #2388
Applications open Internship

Data Analyst

Chubb

  • Bangalore, Karnataka, India
  • 6 LPA - 9 LPA
  • Fresher (0-1 Yrs)
  • Posted Oct 29, 2026
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About the role

Chubb is a global leader in insurance, operating in 54 countries and serving a diverse client base with commercial, personal, and specialty products. The firmโ€™s strength lies in its extensive product suite, strong distribution network, and robust financial backing. In India, Chubb has grown to a workforce of over 2,500 professionals and is recognized as a Great Place to Workยฎ for three consecutive years, reflecting a culture that values collaboration, innovation, and continuous learning. The company is on a digital transformation journey, investing heavily in analytics, automation, and modern engineering practices to stay ahead in a rapidly evolving risk landscape. The role of Analyst โ€“ Risk is positioned at the intersection of data, analytics, and insurance underwriting. As a fresher analyst, you will be responsible for producing risk accumulation analyses, supporting the global exposure database, and delivering insights that influence underwriting decisions. You will work closely with crossโ€‘functional teamsโ€”including design, engineering, quality assurance, and operationsโ€”to develop risk tools, automate workflows, and ensure highโ€‘quality data capture. The position offers exposure to cuttingโ€‘edge AI promptโ€‘engineering techniques and the chance to contribute to strategic risk management initiatives. **Key Responsibilities** 1. Generate comprehensive risk accumulation reports for senior management, consolidating data from multiple sources. 2. Maintain and enhance the global exposure database, monitoring emerging risks and trends. 3. Conduct adโ€‘hoc research and industry risk analysis to support underwriting decisions. 4. Design and implement promptโ€‘engineering strategies to improve AIโ€‘driven tasks. 5. Collaborate with design, engineering, QA, and operations teams to deliver riskโ€‘focused tools and solutions. 6. Identify automation opportunities to streamline data capture and analysis workflows. 7. Coordinate with onshore and internal teams to ensure timely project delivery and issue resolution. 8. Prepare clear visualizations and presentations using Power BI or Qlik Sense for diverse stakeholders. 9. Continuously improve data quality through validation, cleansing, and documentation. 10. Stay updated on regulatory changes and emerging risk factors affecting the insurance portfolio. **Tech Stack**: SQL, Python/R, Microsoft Excel (VBA), MS Access, Microsoft SQL Server or Snowflake, Power BI/Qlik Sense, basic AI promptโ€‘engineering concepts. **Growth Path**: Successful analysts can progress to Senior Analyst, Risk Manager, and eventually to roles such as Underwriting Lead or Head of Risk Analytics, with opportunities to work on global projects and crossโ€‘border teams. **Why Join Chubb?** The company offers a startโ€‘upโ€‘like culture within a stable, worldโ€‘class organization, providing exposure to realโ€‘world insurance challenges, robust learning programs, and a supportive environment that rewards innovation and ownership. Employees benefit from flexible work options, comprehensive health coverage, and a clear career progression roadmap.

Eligibility & process

Who can apply

Graduates (B.Tech/B.E., B.Sc., B.Com, MBA) from any stream with a minimum CGPA/percentage of 6.5/65%; batch years 2023โ€‘2025; no active backlogs; strong analytical mindset; good communication skills; willingness to learn insurance and data analytics.

Skills & stack

SQL Python Excel (Vba) Power BI Qlik Sense Data Analysis Risk Modeling Business Acumen

Selection process

  1. Round 1: Application Screening
  2. Round 2: Technical/Functional Assessment (HackerRank or case study)
  3. Round 3: Managerial Interview (risk & analytics focus)
  4. Round 4: HR Interview

Prep kit

20 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
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, Python, Excel (Vba), Power BI, Qlik Sense, Data Analysis, Risk Modeling, Business Acumen) & 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 Chubb Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 5
What is the difference between WHERE and HAVING clauses in SQL? Answer
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
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
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
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
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.
Behavioural & HR questions 3
Why do you want to join Chubb as a Data Analyst?
Highlight Chubb'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.
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?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Chubb 6 LPA - 9 LPA
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