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REQUIREMENT_ID_62 β€’ 3-DAY_ACTIVE_POLICY

Analyst – Actuarial Services

Company
Company ejgk.fa.em2.oraclecloud.com
Type
Opportunity Type Internship
Salary
Stipend / Salary 6-8 LPA
Location
Location Bangalore, Karnataka, India
Posted Date
Posted Date Today
Statistical analysis Data modeling Excel SQL R Python SAS Tableau Power BI Problem solving Communication Attention to detail
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Placement Papers for Analyst Role Open Resource β†—
Curated set of past placement papers to help you practice quantitative and logical reasoning required for the analyst position.
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Interview Experiences and Tips Open Resource β†—
First‑hand interview experiences and preparation tips that cover the typical rounds for analyst roles at this company.
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Recruitment Process Guide Open Resource β†—
A comprehensive guide on the recruitment stages, question patterns, and preparation strategies for analyst candidates.
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Algorithm Practice Problems Open Resource β†—
A collection of coding and algorithm problems to sharpen problem‑solving skills essential for technical interviews.

Graduate or Post Graduate in Mathematics, Statistics, Actuarial Science, Economics, Engineering (with strong math background) or related fields; Minimum 60% aggregate (or CGPA 6.0/10); No active backlogs; Freshers or up to 1 year of relevant experience; Batch year 2023‑2025 preferred.

1
Round 1: Online Aptitude Test
2
Round 2: Technical Interview
3
Round 3: HR Interview
KPMG Global Services (KGS) is a leading professional services firm that blends deep industry expertise with cutting‑edge technology to help clients navigate complex business challenges. With a strong presence in India, KGS offers a collaborative environment where fresh talent can work alongside seasoned consultants on high‑impact projects across finance, risk, and analytics. The firm is renowned for its commitment to continuous learning, robust mentorship programs, and a culture that encourages innovative thinking. The Analyst – Actuarial Services role is designed for recent graduates who have a solid foundation in mathematics, statistics, and data analysis. As an Analyst, you will be part of the actuarial team that supports insurance, banking, and financial services clients in building predictive models, assessing risk, and delivering actionable insights. This position provides a unique opportunity to apply theoretical knowledge to real‑world problems while gaining exposure to industry‑leading tools and methodologies. Key responsibilities include: 1. Collecting, cleaning, and validating large data sets from multiple sources. 2. Performing statistical analysis and developing predictive models using R, Python, or SAS. 3. Assisting senior actuaries in pricing, reserving, and capital modeling projects. 4. Preparing detailed analytical reports and visualizations for client presentations. 5. Conducting exploratory data analysis to identify trends and anomalies. 6. Supporting the development of automated dashboards using Tableau or Power BI. 7. Collaborating with cross‑functional teams such as finance, underwriting, and IT to ensure data integrity. 8. Keeping abreast of regulatory changes and industry best practices. 9. Participating in knowledge‑sharing sessions and continuous learning initiatives. 10. Contributing to process improvement initiatives within the actuarial practice. The tech stack typically includes Excel, SQL, R, Python, SAS, and data‑visualisation tools like Tableau. Career progression follows a clear path: Analyst β†’ Senior Analyst β†’ Manager β†’ Senior Manager β†’ Director, with regular performance reviews and opportunities for certifications (e.g., SOA, CAS). Joining KGS means working in a supportive environment that values work‑life balance, offers flexible work arrangements, and provides access to world‑class training resources. The firm’s global network opens doors to international assignments and exposure to diverse client portfolios, making it an ideal launchpad for a rewarding actuarial career.

ejgk.fa.em2.oraclecloud.com 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 🎯
ejgk.fa.em2.oraclecloud.com Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for ejgk.fa.em2.oraclecloud.com 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 (Statistical analysis, Data modeling, Excel, SQL, R, Python, SAS, Tableau, Power BI, Problem solving, Communication, 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
ejgk.fa.em2.oraclecloud.com 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 ejgk.fa.em2.oraclecloud.com as a Analyst – Actuarial Services?
Preparation Tip: Highlight ejgk.fa.em2.oraclecloud.com's market reputation, recent tech innovations, and how your skills in Statistical 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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