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REQUIREMENT_ID_217 β€’ 3-DAY_ACTIVE_POLICY

Data Analyst

Company
Company OLTOWNS
Type
Opportunity Type Internship
Salary
Stipend / Salary Not disclosed
Location
Location Greater Bengaluru Area
Posted Date
Posted Date Today
SQL Excel Power BI Tableau Python Data cleaning Statistical analysis Data visualization Business acumen Problem solving
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Aptitude Practice Questions Open Resource β†—
Curated set of quantitative and logical problems to sharpen the reasoning skills required for the first screening round.
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Company Interview Preparation Guide Open Resource β†—
Comprehensive guide covering typical interview formats, sample questions and tips to perform well in data‑analytics interviews.
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Comprehensive Interview Prep Resource Open Resource β†—
Extensive collection of interview experiences, mock questions and strategies to help candidates ace technical and HR rounds.
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Algorithm and Data Structure Problems Open Resource β†—
Practice platform for coding challenges that enhance problem‑solving abilities essential for technical assessments.

Graduates (B.Tech/B.E., B.Sc., BCA, B.Com) in Computer Science, Information Technology, Electronics, Statistics, Mathematics or related fields; Minimum 60% aggregate (or CGPA 6.5/10); Freshers or candidates with up to 2 years of experience; Batch year 2022‑2025; No active backlogs at the time of joining; Strong analytical mindset and willingness to learn.

1
Round 1: Aptitude & Logical Reasoning Test
2
Round 2: Technical Interview (SQL, Excel, Python, case studies)
3
Round 3: HR Interview (fitment, communication, career goals)
OLTOWNS is an emerging retail‑technology startup that focuses on building data‑driven solutions for brick‑and‑mortar stores across India. Founded by a team of ex‑e‑commerce and supply‑chain professionals, the company leverages advanced analytics to help retailers optimise inventory, improve sales forecasting and enhance customer experience. With its headquarters in Bengaluru, OLTOWNS has rapidly expanded its footprint to several Tier‑2 and Tier‑3 cities, partnering with over 200 stores and processing millions of transaction records every month. The firm prides itself on a collaborative culture where every employee’s insight can shape product road‑maps and business strategies. As a Data Analyst at OLTOWNS, you will be at the heart of the decision‑making engine. You will work closely with product, operations and sales teams to translate raw business data into actionable insights. Your day‑to‑day responsibilities will include extracting data from multiple sources, cleaning and validating it, and building visual dashboards that surface key performance indicators for senior leadership. You will also be expected to automate repetitive reporting tasks, ensuring that stakeholders receive timely and accurate information without manual effort. Key Responsibilities: 1. Collect, clean, validate, and analyse business and operational data from sales, inventory, procurement and store‑level systems. 2. Prepare daily, weekly and monthly MIS reports that highlight performance against targets. 3. Develop and maintain interactive dashboards (Power BI/Tableau) for key business KPIs. 4. Identify trends, patterns, anomalies and growth opportunities through statistical analysis. 5. Track store and overall business performance against set goals and provide variance explanations. 6. Support management with data‑driven recommendations for strategic initiatives. 7. Collaborate with cross‑functional teams to understand requirements and translate them into analytical solutions. 8. Automate repetitive reporting and data‑processing workflows using Python/SQL scripts. 9. Ensure data accuracy, consistency and integrity across all reports and dashboards. 10. Present analytical findings in a clear, concise manner to both technical and non‑technical audiences. Tech Stack: SQL, Python (pandas, numpy), Excel, Power BI/Tableau, Git for version control, basic knowledge of cloud data warehouses (Snowflake/BigQuery) is a plus. Growth Path: Starting as an Analyst, high performers can progress to Senior Analyst, then to Analytics Lead or Product Analyst roles, eventually moving into Data Science or Business Intelligence Management positions. The company encourages continuous learning through internal workshops, certifications and mentorship programs. Why Join OLTOWNS? You will be part of a fast‑growing startup that values data as a strategic asset. The role offers exposure to end‑to‑end analytics workflows, direct interaction with senior leadership, and the chance to make a tangible impact on retail businesses across India. If you are passionate about turning numbers into stories and love a dynamic, collaborative environment, OLTOWNS is an ideal place to launch your analytics career.

OLTOWNS 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 🎯
OLTOWNS Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for OLTOWNS 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, Excel, Power BI, Tableau, Python, Data cleaning, Statistical analysis, Data visualization, Business acumen, Problem solving) & 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
OLTOWNS 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 OLTOWNS as a Data Analyst?
Preparation Tip: Highlight OLTOWNS'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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