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REQUIREMENT_ID_1603 β€’ 3-DAY_ACTIVE_POLICY

Remote Junior Data Analyst

Company
Company Urbanhiring
Type
Opportunity Type Internship
Salary
Stipend / Salary β‚Ή35,000–₹50,000/month
Location
Location Navi Mumbai / Remote
Posted Date
Posted Date Oct 06, 2026
Excel SQL Python data visualization Tableau Power BI statistical analysis communication problem solving attention to detail
πŸ“–
Aptitude and Logical Reasoning Practice Open Resource β†—
Helps sharpen analytical thinking and problem‑solving skills essential for data analysis roles.
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Interview Preparation for Data Roles Open Resource β†—
Provides insights into common interview questions and best practices for data analyst positions.
πŸ“–
Data Analytics Study Guide Open Resource β†—
Offers structured learning paths for foundational data analytics concepts and tools.
πŸ“–
Coding Challenges for Data Analysis Open Resource β†—
Builds coding proficiency in Python and SQL, crucial for data manipulation and analysis tasks.

Bachelor’s degree in any discipline (preferably Computer Science, Statistics, Economics, Business Analytics, or related fields). Minimum 60% or 6.5 CGPA. No backlogs allowed. Batch year 2026.

1
Round 1: Technical (coding and aptitude)
2
Round 2: HR
3
Round 3: Managerial
UrbanHiring is a rapidly growing recruitment platform that bridges the gap between talented professionals and leading organizations across India. With a strong focus on technology, analytics, and data-driven hiring, the company has built a reputation for delivering innovative solutions and a seamless candidate experience. The team is known for its collaborative culture, continuous learning environment, and a commitment to fostering professional growth for every member. The Remote Junior Data Analyst role is designed for freshers or professionals with up to two years of experience who are passionate about turning raw data into actionable insights. As a junior analyst, you will work closely with the analytics team to collect, clean, and analyze data from various sources. Your findings will be translated into clear, concise reports and visualizations that inform business decisions across the organization. Key Responsibilities: 1. Collect and ingest data from internal and external sources. 2. Clean, transform, and validate data to ensure accuracy and integrity. 3. Perform exploratory data analysis to uncover trends and patterns. 4. Build dashboards and visualizations using tools like Tableau or Power BI. 5. Prepare and present data insights to stakeholders in a clear and compelling manner. 6. Collaborate with cross-functional teams on data-driven projects. 7. Maintain documentation of data sources, processes, and methodologies. 8. Identify opportunities for process automation and data quality improvements. 9. Support ad‑hoc analysis requests from business units. 10. Stay updated on industry best practices and emerging analytics tools. Tech Stack: Excel, SQL, Python (pandas, numpy), Tableau/Power BI, basic R, and data cleaning libraries. Growth Path: Starting as a Junior Data Analyst, you can progress to Senior Analyst, Data Scientist, Analytics Manager, or even lead a data analytics team. The company encourages skill development through mentorship, training programs, and exposure to diverse projects. Why Join UrbanHiring? - Work from home with flexible hours. - Direct impact on business decisions through data insights. - Mentorship from experienced analysts and data scientists. - Continuous learning opportunities and skill development. - A supportive, inclusive culture that values innovation and teamwork. UrbanHiring’s remote-first approach ensures you can balance professional growth with personal commitments, making it an ideal environment for fresh talent looking to build a career in data analytics.

Urbanhiring 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 🎯
Urbanhiring Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for Urbanhiring 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 (Excel, SQL, Python, data visualization, Tableau, Power BI, statistical analysis, communication, problem solving, 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
Urbanhiring 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 Urbanhiring as a Remote Junior Data Analyst?
Preparation Tip: Highlight Urbanhiring's market reputation, recent tech innovations, and how your skills in Excel 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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