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REQUIREMENT_ID_135 β€’ 3-DAY_ACTIVE_POLICY

Data Analyst

Company
Company S&P Global
Type
Opportunity Type Internship
Salary
Stipend / Salary β‚Ή7–11 LPA
Location
Location Gurgaon / Hyderabad
Posted Date
Posted Date Today
Data analysis SQL Excel Python Tableau PowerBI Statistical analysis Data visualization Problem solving Communication
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Aptitude Practice Questions Open Resource β†—
Covers quantitative, logical and verbal sections to help you ace the online screening test.
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Technical Interview Preparation Guide Open Resource β†—
Offers coding patterns, SQL queries and data‑analysis concepts commonly asked in data analyst interviews.
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Data Analyst Interview Guide for S&P Global Open Resource β†—
Specific insights, sample questions and role‑specific tips for S&P Global’s data analyst hiring process.
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Algorithm & Data Structure Problem Set Open Resource β†—
Practice platform to sharpen problem‑solving skills essential for technical rounds.

Graduates (B.Tech/B.E., B.Sc., B.Com, MCA, or equivalent) from any stream; minimum 60% aggregate (or CGPA 6.0/10); passing year 2025 or 2026; no active backlogs at the time of joining; strong analytical mindset and willingness to learn.

1
Round 1: Online Aptitude Test (Logical Reasoning, Quantitative, Verbal)
2
Round 2: Technical Interview (SQL, Python, Data handling, Case studies)
3
Round 3: HR Interview (fitment, motivation, salary expectations)
S&P Global is a leading provider of transparent and independent credit ratings, benchmarks, analytics and data solutions for the global financial markets. With a presence in more than 30 countries, the firm helps investors, corporations and governments make informed decisions by delivering high‑quality data and insights. The company’s culture is built around integrity, collaboration and continuous learning, encouraging employees to challenge the status quo and drive innovation in the financial data space. As a fresher‑friendly organization, S&P Global invests heavily in training programs, mentorship and clear career pathways, making it an attractive launchpad for young talent. The Data Analyst role is designed for recent graduates who are eager to dive into the world of data‑driven decision making. You will work closely with senior analysts and product owners to collect, clean, and interpret large datasets that power S&P Global’s flagship products. The position offers exposure to industry‑leading tools and methodologies, enabling you to develop a solid foundation in data analytics while contributing to real‑world business outcomes. Key Responsibilities: 1. Collate, clean, and validate large volumes of data according to defined guidelines. 2. Perform exploratory data analysis to uncover trends, anomalies, and insights. 3. Load processed data into internal work tools and maintain data pipelines. 4. Understand dataset structures, workflow dependencies, and documentation standards. 5. Meet individual and team targets while ensuring high‑quality deliverables. 6. Suggest improvements to data collection methods and product features. 7. Participate in ad‑hoc projects, delivering results within stipulated timelines. 8. Troubleshoot data‑related issues and provide timely support to peers. 9. Assist in refining departmental processes and workflows. 10. Contribute to building technical expertise within the team through knowledge sharing. Tech Stack: SQL, Python (pandas, numpy), Excel, Tableau/Powerβ€―BI, Git, and internal data‑management platforms. The role offers a clear growth pathβ€”from Analyst to Senior Analyst, then to Data Scientist or Product Ownerβ€”supported by regular performance reviews and skill‑upgradation programs. Joining S&P Global means working in a globally recognized brand, gaining exposure to financial data at scale, and building a network of seasoned professionals. The supportive environment, competitive salary, and emphasis on work‑life balance make it an excellent starting point for a data‑centric career.

S&P Global 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 🎯
S&P Global Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for S&P Global 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, SQL, Excel, Python, Tableau, PowerBI, Statistical analysis, Data visualization, 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
S&P Global 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 S&P Global as a Data Analyst?
Preparation Tip: Highlight S&P Global'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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