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REQUIREMENT_ID_1401 β€’ 3-DAY_ACTIVE_POLICY

Data Analyst (Remote)

Company
Company Hirecrap
Type
Opportunity Type Internship
Salary
Stipend / Salary 3.5 LPA
Location
Location Remote
Posted Date
Posted Date Sep 28, 2026
Data Analysis Statistical Methods Data Visualization Python R SQL AI Model Evaluation Benchmarking Problem Solving Communication
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Aptitude Practice Questions Open Resource β†—
Curated quantitative and logical reasoning problems to sharpen the analytical skills required for the online test at hirecrap.com.
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Company Interview Preparation Guide Open Resource β†—
Comprehensive guide covering typical interview patterns, technical topics, and HR questions for roles similar to Data Analyst at hirecrap.com.
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Comprehensive Interview Prep Resource Open Resource β†—
Extensive collection of interview experiences, sample questions, and preparation tips useful for landing a data‑focused role at hirecrap.com.
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Algorithm and Data Structure Problem Set Open Resource β†—
A wide range of coding challenges to improve problem‑solving speed and accuracy, essential for technical interviews at hirecrap.com.

Graduates (B.Tech/B.E., B.Sc., MCA) from any stream with a strong foundation in statistics or data analysis. Minimum aggregate 60% (or CGPA 6.0/10). Eligible batch years: 2025, 2026, 2027. No active backlogs at the time of joining. Candidates should have basic knowledge of AI/ML concepts and be comfortable working remotely.

1
Round 1: Online Aptitude & Logical Reasoning Test
2
Round 2: Technical Interview (focus on statistics, data visualization, AI benchmarking)
3
Round 3: HR Interview (cultural fit, communication skills)
Hirecrap.com is an emerging technology staffing firm that partners with global leaders in the Technology, Information and Internet sectors. With a focus on delivering high‑impact talent solutions, the company has built a reputation for fast, reliable hiring and a culture that encourages continuous learning. Their client portfolio includes multinational AI research labs, cloud service providers, and data‑driven product companies, giving employees exposure to cutting‑edge projects across the AI ecosystem. The organization prides itself on a collaborative environment where analysts, engineers, and product managers work side‑by‑side to solve real‑world problems. The Data Analyst role is a full‑time, remote position that serves as a Subject Matter Expert for Data & Statistical Chart Analysis within AI Benchmarking. As a key member of the analytics team, you will evaluate statistical datasets, interpret complex visualizations, and validate the integrity of benchmarking reports that compare AI model performance across diverse scenarios. Your insights will directly influence how the client measures progress, identifies bottlenecks, and sets future research directions. Key Responsibilities: 1. Evaluate and interpret statistical data and visual representations to assess AI performance benchmarks. 2. Analyze trends, anomalies, and correlations in AI benchmarking datasets. 3. Validate data integrity and consistency across benchmarking reports. 4. Collaborate with cross‑functional teams to refine benchmarking methodologies. 5. Document findings and present insights to stakeholders in clear, non‑technical language. 6. Develop and maintain dashboards that track benchmark metrics over time. 7. Conduct root‑cause analysis for performance deviations and recommend corrective actions. 8. Stay updated with the latest AI evaluation frameworks and incorporate best practices. 9. Assist in preparing technical white‑papers and client presentations. 10. Mentor junior analysts on statistical techniques and visualization tools. Tech Stack: Python (pandas, numpy, matplotlib, seaborn), R, SQL, Tableau/PowerBI, Jupyter notebooks, Git, and familiarity with AI performance metrics such as BLEU, ROUGE, F1‑score, latency, and throughput. Growth Path: Starting as a Data Analyst, high performers can progress to Senior Analyst, Benchmarking Lead, or AI Analytics Manager within 2‑3 years, with opportunities to transition into data science or product analytics roles based on interest and skill development. Why Join Hirecrap.com: The role offers the flexibility of remote work while providing exposure to world‑class AI projects. You will work with a global client base, gain deep expertise in AI benchmarking, and benefit from a supportive culture that values upskilling, mentorship, and work‑life balance. The company’s commitment to merit‑based growth ensures that your contributions are recognized and rewarded.

Hirecrap 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 🎯
Hirecrap Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for Hirecrap 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 Analysis, Statistical Methods, Data Visualization, Python, R, SQL, AI Model Evaluation, Benchmarking, Problem Solving, 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
Hirecrap 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 Hirecrap as a Data Analyst (Remote)?
Preparation Tip: Highlight Hirecrap's market reputation, recent tech innovations, and how your skills in Data Analysis 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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