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REQUIREMENT_ID_275 โ€ข 3-DAY_ACTIVE_POLICY

Data Analyst

Company
Company Data Eminence
Type
Opportunity Type Internship
Salary
Stipend / Salary 3-5 LPA
Location
Location Remote
Posted Date
Posted Date Today
Data cleaning Data visualization SQL Excel Python Pandas NumPy Power BI Tableau Statistical analysis Business acumen Communication Attention to detail
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Aptitude Practice Questions Open Resource โ†—
Helps you sharpen quantitative and logical reasoning skills essential for the initial screening test.
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Company Interview Preparation Guide Open Resource โ†—
Provides insights into common interview formats and questions asked by Indian tech firms, useful for the technical round.
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Data Analyst Interview Guide for Data Eminence Open Resource โ†—
Specific preparation material covering roleโ€‘specific topics, sample questions, and tips for Data Eminence interviews.
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Algorithm Problem Set Open Resource โ†—
Offers practice problems to improve problemโ€‘solving speed and coding proficiency, beneficial for technical assessments.

Bachelorโ€™s degree in Data Science, Statistics, Mathematics, Economics, Computer Science, Business Analytics or related field; minimum 60% aggregate; graduating batch 2023โ€‘2026; no active backlogs at the time of joining; strong analytical mindset and willingness to learn.

1
Round 1: Online Aptitude & Logical Reasoning Test
2
Round 2: Technical Interview (SQL, Python, Data Visualization)
3
Round 3: HR Interview
Data Eminence is a fastโ€‘growing analytics consultancy that helps enterprises turn raw data into strategic advantage. Founded by a team of seasoned data scientists, the company blends traditional statistical methods with cuttingโ€‘edge AI tools to deliver actionable insights across sectors such as finance, eโ€‘commerce, and healthcare. With a culture that encourages continuous learning, Data Eminence invests heavily in upโ€‘skilling its talent through certifications, internal hackathons, and mentorship programs. The firmโ€™s remoteโ€‘first policy allows employees to work from anywhere in India while staying connected through collaborative platforms and regular virtual meetโ€‘ups. As a Data Analyst (Contract) at Data Eminence, you will be at the heart of the dataโ€‘toโ€‘decision pipeline. You will ingest raw datasets, cleanse and transform them, and build visual narratives that guide product, marketing, finance, and technology teams. The role offers handsโ€‘on exposure to the full analytics stack โ€“ from Excelโ€‘based explorations to SQL queries, Python scripting, and modern BI tools such as Power BI and Tableau. You will also get a chance to experiment with AIโ€‘powered analytics platforms, automating routine tasks and uncovering hidden patterns. Key Responsibilities: 1. Collect, aggregate, and validate data from multiple internal and external sources. 2. Perform data cleaning, normalization, and enrichment to ensure highโ€‘quality inputs. 3. Conduct exploratory analysis to identify trends, outliers, and business opportunities. 4. Design and develop interactive dashboards and visual reports using Power BI or Tableau. 5. Generate adโ€‘hoc analytical reports to support strategic decisionโ€‘making. 6. Collaborate with crossโ€‘functional teams to translate business questions into analytical solutions. 7. Document data pipelines, methodologies, and findings for reproducibility. 8. Explore and prototype AIโ€‘driven analytics and automation tools to improve efficiency. 9. Communicate insights clearly through presentations and written summaries. 10. Maintain data accuracy and adhere to governance standards. Tech Stack: Microsoft Excel, SQL, Python (Pandas, NumPy), Power BI, Tableau, basic statistical methods, relational databases, and exposure to AIโ€‘analytics platforms. Growth Path: Starting as a contract analyst, high performers can transition to fullโ€‘time roles, progress to Senior Analyst, then to Analytics Lead or Product Analytics Manager, with opportunities to specialize in data engineering or AIโ€‘driven analytics. Why Join Data Eminence? You will work on realโ€‘world projects that impact business outcomes, gain mentorship from industry veterans, and enjoy the flexibility of remote work while being part of a collaborative, innovationโ€‘driven community. The companyโ€™s commitment to professional development ensures you stay ahead of the rapidly evolving data landscape.

Data Eminence โ€” Data Analytics & SQL Interview Guide

Previously asked questions, exam syllabus, coding benchmarks & round strategy.

APTITUDE & LOGIC ๐Ÿ“–
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 โ†—
COMPANY GUIDE ๐ŸŽฏ
Data Eminence Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for Data Eminence and off-campus tech roles.

Open Resource โ†—
MOCK TESTS & PAPERS ๐Ÿ“
Comprehensive Interview Prep Resources & Syllabus

Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.

Open Resource โ†—
CODING PRACTICE ๐Ÿ’ป
Algorithm and Data Structure Problem Set

Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.

Open Resource โ†—
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 cleaning, Data visualization, SQL, Excel, Python, Pandas, NumPy, Power BI, Tableau, Statistical analysis, Business acumen, 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
Data Eminence 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 โ–ผ
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 โ–ผ
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 โ–ผ
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 โ–ผ
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 โ–ผ
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 Data Eminence as a Data Analyst?
Preparation Tip: Highlight Data Eminence's market reputation, recent tech innovations, and how your skills in Data cleaning 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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