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REQUIREMENT_ID_353 • 3-DAY_ACTIVE_POLICY

Data Analyst

Company
Company Genmills
Type
Opportunity Type Full-Time Job
Salary
Stipend / Salary 4 LPA
Location
Location Powai, Mumbai, MH
Posted Date
Posted Date Today
Time series modelling ARIMA Exponential smoothing Causal forecasting SQL PLSQL Tableau Power BI Looker Python R Excel GCP AWS Azure Data visualization Statistical analysis Supply chain fundamentals Stakeholder management Problem solving
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Aptitude and Logical Reasoning Practice Open Resource ↗
Helps you sharpen quantitative and logical skills essential for the first screening round at General Mills.
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Company Interview Preparation Guide Open Resource ↗
Provides insights into typical interview patterns and common questions asked by large FMCG firms like General Mills.
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Interview Coaching and Sample Questions Open Resource ↗
Offers curated interview experiences, mock questions and tips that align with demand‑forecasting roles.
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Algorithmic Problem‑Solving Practice Open Resource ↗
Strengthens coding and analytical thinking required for technical rounds involving Python/R and data manipulation.

Minimum: Bachelor’s degree in Operations Research, Statistics, Supply Chain, Industrial Engineering or related field. Minimum aggregate 60% (or CGPA 6.0/10). No active backlogs at the time of joining. Recent graduates (2022‑2025) are preferred. Candidates should have 1‑2 years of data‑analysis experience or relevant internships.

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Round 1: Aptitude & Logical Reasoning
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Round 2: Technical interview (SQL, Python/R, forecasting concepts)
3
Round 3: HR interview (fit, communication, career aspirations)
General Mills India, the Indian arm of the global food powerhouse, exists to make food the world loves. The company’s mission goes beyond delivering tasty products – it is a place that encourages learning, embraces diverse perspectives and constantly re‑imagines possibilities. Employees are described as bold thinkers with big hearts, who challenge each other and grow together. The culture is built around purpose, sustainability and a relentless drive to be the undisputed leader in the food industry. The Analyst – Demand Forecasting role is a critical part of the Demand Planning function. Working on a 1.30 pm to 10.30 pm shift, the analyst will design, implement and continuously improve forecasting solutions that enhance accuracy and support business decisions. The role blends statistical modelling, data engineering and stakeholder management, offering a perfect launchpad for fresh graduates who love numbers and enjoy translating insights into actionable plans. **Key Responsibilities** 1. Build, validate and maintain time‑series and causal forecasting models (ARIMA, exponential smoothing, regression, etc.). 2. Analyse model outputs, generate change‑over reports and present insights to business stakeholders. 3. Conduct descriptive analysis on large data sets to uncover patterns, trends and root‑cause factors. 4. Track performance metrics such as forecast accuracy, bias and variance; recommend corrective actions. 5. Extract, transform and load data from primary and secondary sources using SQL/PLSQL and cloud platforms (GCP, AWS, Azure). 6. Develop interactive dashboards in Tableau/Power BI/Looker for real‑time visibility of demand forecasts. 7. Collaborate closely with data‑science and supply‑chain teams to identify automation opportunities and validate model enhancements. 8. Engage with cross‑functional stakeholders to ensure alignment on forecast assumptions and business plans. 9. Document forecasting methodology, standard operating procedures and best‑practice guidelines. 10. Participate in continuous improvement initiatives, including root‑cause analysis (RCA) and process redesign. **Tech Stack**: Python, R, SQL/PLSQL, Tableau, Power BI, Looker, GCP/AWS/Azure, Excel, statistical libraries (statsmodels, scikit‑learn). **Growth Path**: Successful analysts can progress to Senior Analyst – Demand Planning, then to Demand Planning Manager, and eventually to Head of Supply Chain Analytics. The role offers exposure to end‑to‑end supply‑chain processes, advanced analytics, and leadership opportunities. **Why Join**: You will work in a purpose‑driven organization that values innovation, offers mentorship from seasoned supply‑chain professionals, and provides a collaborative environment where fresh ideas are welcomed. The hybrid setup in Powai gives you access to modern office facilities while allowing flexibility. The company’s commitment to employee development, competitive compensation and a clear career ladder makes it an attractive choice for ambitious graduates.

Genmills — 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 🎯
Genmills Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for Genmills 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 (Time series modelling, ARIMA, Exponential smoothing, Causal forecasting, SQL, PLSQL, Tableau, Power BI, Looker, Python, R, Excel, GCP, AWS, Azure, Data visualization, Statistical analysis, Supply chain fundamentals, Stakeholder management, 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
Genmills 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 Genmills as a Data Analyst?
Preparation Tip: Highlight Genmills's market reputation, recent tech innovations, and how your skills in Time series modelling 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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