Aarti Industries interview questions

In a campus place ment it is very easy ti crack The process is quick, they expect a reply from you on the same day as your interview day so be prepared

**Application Process:** Applied through campus referral. The process took about **2.5 weeks** and consisted of **3 rounds**. **Interview Rounds:** 1. **Aptitude & Excel Assessment (Online)** First round was a basic aptitude + Excel skills test. It included case-based numerical questions and Excel functions (VLOOKUP, Pivot Tables, IF statements). Fairly standard but time-sensitive. 2. **Technical Interview (Virtual)** Conducted by the Data Science Manager. Questions covered: * Project walkthrough (I spoke about an inventory cost variance dashboard I’d built in Power BI) * Concepts in regression, data cleaning, KPI building * Tools: SQL joins, DAX vs. Excel formulas, use of Power BI filters Also had 2 short case scenarios: "How would you estimate demand for a product with incomplete data?" and "Design a dashboard for plant managers tracking efficiency." 3. **HR + Behavioral Round (Phone Call)** Final round was with HR. Asked about: * Relocation flexibility (the role was Mumbai-based) * Career goals and preferred domains (Manufacturing, Supply Chain, etc.) * Standard situational questions: “A time you handled a data error before a deadline,” etc. **Overall Experience:** Smooth and professional. The interviewers were friendly and seemed genuinely interested in data quality and domain fit. They appreciated real-world project examples, especially where I linked analytics with operational savings. **Tips for Future Candidates:** * Brush up on Excel and Power BI – dashboards and use cases matter more than textbook definitions * Be ready with 2–3 strong data projects where you directly influenced business decisions * Understand basic manufacturing KPIs: cycle time, cost per unit, defect rates, etc. **Result:** Got the offer and accepted. Solid place for early-career analytics professionals, especially if you're interested in working at the intersection of operations and data