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REQUIREMENT_ID_260 β€’ 3-DAY_ACTIVE_POLICY

Data Analyst

Company
Company ShrinQ Consulting Group
Type
Opportunity Type Internship
Salary
Stipend / Salary 6- 8 LPA approx.
Location
Location India
Posted Date
Posted Date Yesterday
SQL Data Analysis Data Visualization Statistics Business Insights Excel Python Tableau
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Aptitude Practice Questions Open Resource β†—
Curated logical and quantitative problems to sharpen reasoning skills required for the online test.
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Interview Preparation Guide Open Resource β†—
Comprehensive guide covering common interview topics and question patterns for data analyst roles.
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Data Analyst Interview Questions for LTI Open Resource β†—
Specific question bank and answer strategies that align with the interview style of similar consulting firms.
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Algorithm Practice Problems Open Resource β†—
A wide range of coding challenges to improve problem‑solving speed and accuracy for technical rounds.

Bachelor's or Master's degree in Statistics, Applied Mathematics, Computer Science, Economics or a related quantitative field. Minimum 60% aggregate (or CGPA 6.0/10) in the qualifying degree. No active backlogs at the time of joining. Fresh graduates as well as candidates with 1‑2 years of relevant data analysis experience are eligible. Preference given to candidates from the 2023‑2025 batch.

1
Round 1: Online Aptitude Test
2
Round 2: Technical Interview (SQL, Data Analytics, Statistics)
3
Round 3: HR Interview
ShrinQ Consulting Group is a fast‑growing analytics‑focused consulting firm that helps enterprises across manufacturing, retail, and financial services turn raw data into actionable business strategies. Founded a few years ago, the company has built a reputation for delivering high‑impact insights through a blend of statistical rigor and modern visualization techniques. With offices in major Indian metros and a client base that spans startups to Fortune 500 companies, ShrinQ prides itself on a collaborative environment where curiosity is rewarded and continuous learning is part of the daily routine. The firm’s culture revolves around data‑driven decision making, encouraging every employee to ask the right questions and challenge assumptions. Employees enjoy a flat hierarchy, regular knowledge‑sharing sessions, and mentorship programs that accelerate professional growth. Work‑life balance is respected, with flexible timings and occasional remote days, allowing analysts to maintain productivity without compromising personal commitments. **Role Summary** As a Data Analyst at ShrinQ, you will be the analytical backbone for multiple business units. Your primary mission is to translate complex data sets into clear, concise visual stories that empower stakeholders to make informed decisions. You will work closely with product managers, operations heads, and senior leadership to identify pain points, design analytical frameworks, and deliver insights that drive revenue, efficiency, and customer satisfaction. **Key Responsibilities** 1. Understand day‑to‑day business challenges and translate them into analytical problems. 2. Gather, clean, and integrate data from heterogeneous sources such as relational databases, CSV files, and APIs. 3. Perform exploratory data analysis to uncover trends, outliers, and hidden patterns. 4. Develop and maintain SQL queries and stored procedures for recurring reporting needs. 5. Build interactive dashboards and visualizations using tools like Tableau or Powerβ€―BI to present findings in an intuitive manner. 6. Conduct ad‑hoc deep‑dive analyses to answer specific business questions and support strategic initiatives. 7. Document analytical methodology, assumptions, and results to ensure reproducibility and knowledge transfer. 8. Collaborate with cross‑functional teams to implement data‑driven recommendations and monitor their impact. 9. Stay updated with emerging analytics techniques, statistical methods, and visualization best practices. 10. Participate in regular review meetings, presenting insights and actionable recommendations to senior leadership. **Tech Stack**: SQL, Python (pandas, numpy), Excel, Tableau/Powerβ€―BI, basic statistical packages (R or Python’s statsmodels). **Growth Path**: Junior Analyst β†’ Analyst β†’ Senior Analyst β†’ Lead Analyst β†’ Analytics Manager β†’ Director of Analytics. The firm encourages certifications (e.g., Tableau Desktop Specialist, Google Data Analytics) and offers internal training to fast‑track career progression. **Why Join ShrinQ**: You will work on real‑world problems for high‑profile clients, gain exposure to end‑to‑end analytics workflows, and be mentored by industry veterans. The supportive culture, clear promotion ladder, and emphasis on work‑life harmony make ShrinQ an ideal launchpad for ambitious data professionals.

ShrinQ Consulting Group 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 🎯
ShrinQ Consulting Group Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for ShrinQ Consulting Group 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, Data Analysis, Data Visualization, Statistics, Business Insights, Excel, Python, Tableau) & 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
ShrinQ Consulting Group 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 ShrinQ Consulting Group as a Data Analyst?
Preparation Tip: Highlight ShrinQ Consulting Group'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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