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REQUIREMENT_ID_1752 β€’ 3-DAY_ACTIVE_POLICY

Data Analytics Internship

Company
Company Nova Technology
Type
Opportunity Type Internship
Salary
Stipend / Salary 23,000 per month
Location
Location Remote
Posted Date
Posted Date Yesterday
Data cleaning Exploratory Data Analysis Python SQL Excel Data Visualization Tableau Power BI Statistical Modeling Communication
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Aptitude Practice Questions Open Resource β†—
Curated quantitative and logical reasoning problems to sharpen the analytical mindset required for the online test.
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Company Interview Preparation Guide Open Resource β†—
Comprehensive guide covering typical interview formats, common data analytics questions, and tips to present your projects effectively.
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Comprehensive Interview Prep Resources Open Resource β†—
A collection of interview experiences, sample questions, and preparation strategies to help you ace technical and HR rounds.
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Algorithm and Data Structure Problem Sets Open Resource β†—
Practice problems to improve coding proficiency in Python, essential for data manipulation and model building tasks.

Open to Undergraduate and Postgraduate students from Engineering, Arts, Commerce, Sciences & other streams. Final year students or fresh graduates with a minimum of 60% aggregate (or CGPA 6.0/10). No active backlogs at the time of joining. Candidates should have basic knowledge of statistics, data handling, and a keen interest in analytics.

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Round 1: Application shortlisting
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Round 2: Online aptitude & logical reasoning test
3
Round 3: Technical interview focusing on data concepts and case studies
4
Round 4: HR interview assessing fit and motivation
Nova Technology is a fast‑growing data‑centric solutions provider that helps enterprises turn raw information into actionable insights. Founded in 2018, the company has built a reputation for delivering end‑to‑end analytics services ranging from data engineering to predictive modelling for clients in e‑commerce, finance, and healthcare. With a culture that encourages curiosity, continuous learning, and cross‑functional collaboration, Nova Technology has become a preferred destination for young talent looking to make a real impact on business decisions. The Data Analytics Internship, offered as part of the Unstop Summer Internship Fair 2026, is a three‑month, full‑time, work‑from‑home opportunity designed for fresh graduates and final‑year students. Interns will work directly with senior analysts and data scientists on live projects, gaining hands‑on experience with the entire analytics lifecycle – from data ingestion to visual storytelling. The role is ideal for candidates who are comfortable with numbers, love solving puzzles, and are eager to learn modern data tools in a supportive environment. Key Responsibilities: 1. Assist in collecting, cleaning, and processing large datasets sourced from APIs, databases, and spreadsheets. 2. Perform exploratory data analysis (EDA) to uncover trends, patterns, and outliers. 3. Develop interactive dashboards using Tableau or Powerβ€―BI to communicate insights to non‑technical stakeholders. 4. Support senior analysts in building predictive models using Python libraries such as scikit‑learn or statsmodels. 5. Translate business requirements into analytical tasks and propose appropriate methodologies. 6. Document data pipelines, analysis procedures, and model performance metrics for future reference. 7. Participate in regular team stand‑ups, present progress updates, and incorporate feedback. 8. Conduct quality assurance checks to ensure data integrity and accuracy of analytical outputs. 9. Contribute to ad‑hoc data requests and assist in preparing presentation decks for client meetings. 10. Continuously explore emerging analytical tools and techniques to improve workflow efficiency. Tech Stack: Python (pandas, numpy, matplotlib), SQL, Excel, Tableau/Powerβ€―BI, Git, Jupyter Notebook, basic statistical methods. Growth Path: High‑performing interns are often offered a Pre‑Placement Offer (PPO) for a full‑time Analyst role. The internship also provides a Certificate of Completion, a Letter of Recommendation, and valuable exposure to real‑world data problems, laying a strong foundation for a career in data science or business analytics. Why Join Nova Technology? The company offers flexible working hours, a mentorship‑driven environment, and direct access to senior data professionals. Interns get to work on projects that directly influence client strategies, making the experience both rewarding and career‑building. The remote setup ensures a healthy work‑life balance while still fostering a collaborative team spirit through virtual meetings and regular feedback sessions.

Nova Technology 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 🎯
Nova Technology Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for Nova Technology 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 cleaning, Exploratory Data Analysis, Python, SQL, Excel, Data Visualization, Tableau, Power BI, Statistical Modeling, 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
Nova Technology 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 Nova Technology as a Data Analytics Internship?
Preparation Tip: Highlight Nova Technology'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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