Swiggy Off-Campus 2026: Data Scientist

Job Description

Hunger Solved by Data. Logistics Powered by Science.

Data Science at Swiggy is divided into specialized pods like Logistics, Consumer, and Labs. You won’t just be building models in a vacuum; you’ll be solving “traveling salesman” problems at a city-wide scale and using NLP to understand diverse Indian food preferences.

✨ Drive Highlights & Quick Details

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💡 The Role: The Architect of Real-Time Decisions

Swiggy’s data science challenges are unique because they happen in “Real-Time.” Your daily work might include:

• Logistics Optimization: Reducing the “First Mile” (distance to restaurant) and “Last Mile” (distance to customer) using advanced geospatial clustering.
• Demand Forecasting: Predicting order surges during a rainy Friday night in Indiranagar so the system can proactively position delivery partners.
• Recommendation Engines: Personalizing the home screen so a vegan user doesn’t see meat options. You might use Bayesian Inference to predict the probability of an order:$$P(Order | User, Context) = \frac{P(Context | Order, User) \times P(Order | User)}{P(Context | User)}$$
• Pricing Algorithms: Working on “Surge” models that balance demand and supply during peak hours.

📝 Selection Process: The “First Principles” Filter

Swiggy looks for “Full-Stack” Data Scientists—people who can write their own SQL, build the model, and explain the business impact to a Product Manager.

1. Stage 1: Technical Screening (Hackerrank/Internal):
   • Heavy focus on Probability, Statistics, and Python/SQL.
   • Expect 1-2 coding problems involving data manipulation (Pandas/NumPy).
2. Stage 2: Machine Learning Case Study:
   • You’ll be given a “Swiggy-specific” problem. Example: “How would you predict the prep-time for a restaurant that has just joined the platform?”
3. Stage 3: Technical Deep Dive:
   • Questions on model evaluation metrics (RMSE, MAPE, AUC-ROC) and “Why” you chose a specific algorithm over another.
4. Stage 4: Director / Hiring Manager Round:
   • Focus on your “Business Intuition.” They want to know if you understand how your model actually makes Swiggy more profitable.

➡️ How to Apply for Swiggy Data Scientist Role

1. Application Link: Register via the official career portal: Apply Now – Swiggy Off Campus.
2. Resume Tip: Swiggy loves Kaggle rankings or GitHub repos that show end-to-end projects. If you have built an API to serve a model, make sure it’s at the top.
3. Focus on “Impact”: Don’t just say “I built a model.” Say “I built a model that reduced [Metric] by X%.”
4. Practice Case Studies: Research “Supply-Demand Gap” and “Fleet Assignment” problems before your interview.