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REQUIREMENT_ID_1575 • 3-DAY_ACTIVE_POLICY

Junior Data Scientist

Company
Company Cron Labs
Type
Opportunity Type Full-Time Job
Salary
Stipend / Salary 3.5 LPA
Location
Location Bengaluru, Karnataka
Posted Date
Posted Date Yesterday
Python SQL Pandas NumPy scikit‑learn TensorFlow PyTorch data visualization Tableau web scraping ETL statistical analysis machine learning analytical thinking teamwork ownership initiative adaptability
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Aptitude and Reasoning Practice Open Resource ↗
Helps sharpen logical thinking and problem‑solving skills essential for data analysis interviews.
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Interview Preparation Guide Open Resource ↗
Provides insights into common interview questions and best practices for technical interviews.
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Data Science Learning Path Open Resource ↗
Offers curated resources and tutorials to build foundational data science knowledge.
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Coding Challenges Repository Open Resource ↗
Contains a wide range of programming problems to practice algorithmic thinking and coding speed.

Bachelor’s degree in Computer Science, Data Science, Statistics, Engineering, or related field. Minimum 70% aggregate (or equivalent). 0–1 year of relevant experience. Proficiency in Python and SQL. Familiarity with data manipulation libraries (pandas, NumPy) and machine learning frameworks (scikit‑learn, TensorFlow, PyTorch). Strong analytical and problem‑solving skills. No backlog policy specified.

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Round 1: Technical interview – coding & ML concepts
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Round 2: Technical interview – case study/project discussion
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Round 3: HR interview
Cron Labs Solutions Pvt Ltd is a fast‑growing technology firm headquartered in Bengaluru, Karnataka, that specializes in delivering AI‑driven solutions across various verticals such as finance, healthcare, and e‑commerce. With a strong focus on data‑centric product development, the company has built a reputation for leveraging cutting‑edge machine learning models and cloud infrastructure to solve complex business problems. Cron Labs prides itself on a collaborative culture where cross‑functional teams work together to iterate quickly and bring data insights to life. The Junior Data Scientist role is designed for fresh graduates or early‑career professionals with 0–1 year of experience. As a key member of the data science team, you will be responsible for end‑to‑end data workflows—from ingestion and cleaning to modeling and deployment. You will work closely with data engineers, product managers, and senior data scientists to translate business requirements into actionable data solutions. Key responsibilities include: 1. Designing and maintaining data pipelines using cloud platforms such as AWS or Azure. 2. Performing data extraction, transformation, and loading (ETL) tasks. 3. Building interactive dashboards and visualizations using Tableau or Power BI. 4. Scraping web data and integrating it into the data lake. 5. Writing efficient SQL queries for data extraction and manipulation. 6. Developing predictive models with scikit‑learn, TensorFlow, or PyTorch. 7. Conducting statistical analysis to uncover trends and patterns. 8. Collaborating with LLM teams to explore large‑language‑model use cases. 9. Documenting model assumptions, performance metrics, and deployment steps. 10. Communicating findings to stakeholders in clear, concise presentations. The tech stack you’ll work with includes Python, Pandas, NumPy, scikit‑learn, TensorFlow, PyTorch, SQL, Tableau, and cloud services like AWS S3 and Lambda. Growth opportunities are abundant: after proving yourself, you can move into senior data scientist, lead data science, or product manager roles. Why join Cron Labs? The company offers a dynamic work environment, exposure to real‑world data challenges, mentorship from seasoned experts, and a clear career ladder. Employees enjoy flexible working hours, a healthy work‑life balance, and a culture that values continuous learning and innovation. Overall, this role is ideal for data enthusiasts who want to build practical skills, contribute to impactful projects, and grow within a supportive tech ecosystem.

Cron Labs — Data Analytics & SQL Interview Guide

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

APTITUDE & LOGIC 📖
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 ↗
COMPANY GUIDE 🎯
Cron Labs Interview Preparation Corner

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

Open Resource ↗
MOCK TESTS & PAPERS 📝
Comprehensive Interview Prep Resources & Syllabus

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

Open Resource ↗
CODING PRACTICE 💻
Algorithm and Data Structure Problem Set

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

Open Resource ↗
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 (Python, SQL, Pandas, NumPy, scikit‑learn, TensorFlow, PyTorch, data visualization, Tableau, web scraping, ETL, statistical analysis, machine learning, analytical thinking, teamwork, ownership, initiative, adaptability) & 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
Cron Labs 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 ▼
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 ▼
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 ▼
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 ▼
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 ▼
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 Cron Labs as a Junior Data Scientist?
Preparation Tip: Highlight Cron Labs's market reputation, recent tech innovations, and how your skills in Python 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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