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REQUIREMENT_ID_357 β€’ 3-DAY_ACTIVE_POLICY

Data Analyst – AI Consulting

Company
Company Hirecrap
Type
Opportunity Type Internship
Salary
Stipend / Salary 3-5 LPA
Location
Location Remote (India)
Posted Date
Posted Date Today
SQL Excel Python Power BI Tableau data cleaning data visualization analytical thinking communication problem solving
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Aptitude Practice Questions Open Resource β†—
Helps candidates sharpen quantitative and logical reasoning skills essential for the online test at hirecrap.com.
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Company Interview Preparation Guide Open Resource β†—
Provides insights into typical interview formats and common questions asked by hirecrap.com recruiters.
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Comprehensive Interview Prep Resource Open Resource β†—
Covers a wide range of topics from data analysis fundamentals to behavioral questions useful for hirecrap.com interviews.
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Algorithm and Data Structure Problem Set Open Resource β†—
Offers coding practice to strengthen Python and SQL problem‑solving abilities required for the technical round at hirecrap.com.

Bachelor's degree in Engineering, Computer Science, Information Technology, Mathematics, Statistics or related fields; any branch accepted. Minimum 60% aggregate (or CGPA 6.0/10). Fresh graduates from 2023, 2024, 2025 or 2026 batches are eligible. Maximum one active backlog allowed at the time of joining. Strong analytical mindset and good communication skills are mandatory.

1
Round 1: Online Aptitude Test
2
Round 2: Technical Interview (focus on data analysis, SQL and Python)
3
Round 3: HR Interview
TailorFlow AI is a Cambridge‑based enterprise AI services firm that builds custom‑made solutions for complex business challenges. Though its headquarters sit in the UK, the company has a truly global footprint, serving clients across the United Kingdom, South Africa, the Americas and Australia. The business model is heavily asynchronous, allowing team members to work across time zones while still maintaining a few hours of overlap with the client’s geography. This flexibility is a core part of TailorFlow’s culture and makes it an attractive place for professionals who value autonomy and a results‑driven environment. In recent months, TailorFlow has expanded its delivery centre to India, hiring remote analysts, engineers and consultants who can collaborate with the core Cambridge team. The Indian cohort works on the same high‑impact projects, gaining exposure to international standards, cutting‑edge AI research and real‑world deployments. The company prides itself on hiring people who take ownership, approach ambiguity constructively and stay positive while navigating complex problem spaces. The role of Data Analyst – AI Consulting sits at the intersection of data engineering, business analysis and AI solution design. You will partner with consulting and engineering teams to understand client data, assess its suitability for AI use cases and translate insights into actionable recommendations. Your day‑to‑day activities will involve cleaning and exploring both structured and unstructured datasets, defining key performance metrics, supporting model validation, and creating visualisations that are easy for non‑technical stakeholders to digest. You will also act as a bridge between the client’s business objectives and the technical implementation, ensuring that data‑driven decisions are grounded in solid analysis. Key Responsibilities: 1. Explore, clean and analyse structured and unstructured client data sets. 2. Assess data quality, completeness and suitability for AI and machine‑learning use cases. 3. Define relevant metrics and prepare concise analytical summaries for project teams. 4. Support model evaluation, testing and output validation activities. 5. Create visualisations and dashboards that communicate findings to non‑technical stakeholders. 6. Collaborate with consultants and engineers to translate analytical insights into solution decisions. 7. Identify data‑quality issues, document their impact and propose remediation strategies. 8. Maintain clear documentation of data pipelines, assumptions and analytical methods. 9. Stay updated on emerging AI trends and suggest innovative approaches to client problems. 10. Contribute to knowledge‑sharing sessions within the team to uplift overall analytical capability. Tech Stack: SQL, Microsoft Excel, Python (pandas, numpy), Powerβ€―BI, Tableau, basic knowledge of machine‑learning concepts. Growth Path: Starting as a Junior Data Analyst, you can progress to Senior Analyst, then to Data Scientist or AI Consultant, eventually moving into lead or managerial roles as the practice scales. Why Join TailorFlow AI? You will work on real AI implementations for a diverse set of international clients, gain exposure to multiple industries, and receive mentorship from seasoned founders and technical specialists. The remote‑first model offers flexibility, meaningful ownership of deliverables, and rapid career progression in a small, high‑performing team.

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 (SQL, Excel, Python, Power BI, Tableau, data cleaning, data visualization, analytical thinking, communication, 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
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 – AI Consulting?
Preparation Tip: Highlight Hirecrap'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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