Data scientist III

Job Role: Data Scientist 3 – Ads & Monetization / Pricing Optimization

Experience Required: 5–7 years

Location: Bangalore | Karnataka

About Swiggy And The Team

Swiggy is India's leading on-demand delivery platform, leveraging data science and cutting-edge AI to redefine convenience for millions of customers. The Food-DS team works at the intersection of machine learning, advanced architecture, and applied research to shape AI-first systems that directly impact customer experience and business growth. The team values cross-functional collaboration, open sharing of ideas, and continuous innovation to roll out machine learning and AI solutions at scale.

About The Role

As a Data Scientist 3 (DS3), you will act as a Technical Stream Lead within the Ads, Pricing, and Discount Optimization sub-domain. You will take end-to-end ownership of scoping, designing, and delivering complex algorithmic decision engines (typically 2–3 related models or experiments over a quarter). You will operate with high autonomy—translating open-ended monetization and incentive allocation challenges into mathematical and ML frameworks, balancing ROI trade-offs, and driving unit economics (L0/L1/L2 metrics) while mentoring junior data scientists.

What Qualities Are We Looking For

Technical Expertise & Problem Formulation

• Experience & Ownership: 4–6 years of experience building and deploying scalable decisioning engines, causal models, or algorithmic ad-tech architectures in production.
• Problem Formulation: Proven ability to break down open-ended pricing, spend allocation, or ad bidding problems into DS/ML sub-problems, defining appropriate targets, constraints, and objective functions.
• Reinforcement Learning & Decision Systems: Hands-on experience with Contextual Bandits, Multi-Armed Bandits (MAB), Markov Decision Processes (MDPs), Q-Learning, Policy Optimization, and Offline Reinforcement Learning for dynamic ad allocation and coupon targeting.
• Causal Inference & Economics: Deep knowledge of Uplift Modeling, Counterfactual Evaluation, Price Elasticity Modeling, and Causal Inference to measure incremental business lift and avoid deadweight loss.
• Optimization & Decision Engines: Expertise in Constrained Optimization, Mixed-Integer Programming (MIP), Bayesian Optimization, and Budget Allocation frameworks to design production-grade Decision Engines.
• Engineering Excellence: Proficient in distributed processing and execution (PySpark, Python, PyTorch/TensorFlow, CVXPY/Gurobi/SciPy) for real-time and batch optimization systems.
  
  

Execution, Operational Excellence & Leadership

• Technical Stream Leadership: Ability to act as the Single Point of Contact (SPOC) for Ads/Discount optimization streams, guiding DS1/DS2 engineers, managing delivery coherence, and setting stakeholder expectations.
• Domain Metric Ownership: Ability to connect DS levers (e.g., ad CTR, eCPM, take-rate, ROI, gross margin) to core business outcomes, root-causing metric shifts (L2 to L1), and proactively identifying spend efficiency opportunities.
• Operational Excellence: Rigor in maintaining system hygiene owning root-cause analyses (RCAs), minimizing tech debt, optimizing pipeline compute costs, and ensuring auction/pricing stability during peak traffic events (e.g., festivals, IPL).
• Pragmatic Innovation: Capability to adapt state-of-the-art research (e.g., novel bandit architectures, causal uplift methods, offline RL evaluation) pragmatically to Swiggy's scale and operational constraints.
  
  

What Will You Do

• Lead Project Streams: Scope, design, and implement solutions for dynamic pricing, ad ranking/bidding, and discount allocation; write comprehensive approach notes, design docs, and phased experiment plans
• Build Algorithmic Decision Engines: Architect optimization engines combining Contextual Bandits, Causal Uplift Models, and Constrained Optimization to allocate ad slots and promo budgets at scale.
• Drive Metric Accountabilities: Function as tech lead for a sub-domain, owning at least 1 Key Result (KR) and using data insights to justify model decisions to Monetization, Product, and Business teams.
• Elevate Engineering Standards: Implement best practices within your pod—including code reviews, test-driven pipelines, version control, on-call hygiene, and async-first technical documentation.
• Mentor & Collaborate: Actively guide and pair with DS1s and DS2s, streamline cross-functional communication, and contribute to pod-level roadmap discussions and technical publications/blogs.
  
  

Why Join Swiggy

• Impact at Scale: Work on high-velocity systems driving real-time decisions for millions of orders.
• Technical Autonomy: Lead sub-domains end-to-end with the space to introduce state-of-the-art techniques.
• Collaborative Growth: Work in a high-density learning environment alongside cross-functional experts in Engineering, Product, and Business.
  
  

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, disability status, or any other characteristic protected by law.