Data Scientist I (Supply chain optimization)

About Zepto

Zepto is a leading Indian consumer technology company and a pioneer in the fast-growing quick-commerce sector. Founded in 2021, Zepto delivers groceries and everyday essentials to millions of customers within minutes through a technology-driven logistics and supply chain network. The company operates at the intersection of product innovation, data science, and customer experience, building scalable consumer platforms in one of the world’s most dynamic digital markets.

Zepto is backed by prominent global and institutional investors, including General Catalyst, Lightspeed Venture Partners, Nexus Venture Partners, StepStone Group, Avra Ventures, and the California Public Employees’ Retirement System (CalPERS). In its most recent pre-IPO funding round, Zepto raised approximately USD 450 million at a valuation of nearly USD 7 billion, underscoring strong investor confidence in the company’s long-term growth and market leadership.

Responsibilities, aka, what we’d like you to deliver :

• Formulate complex business problems (e.g., routing, scheduling, resource allocation) as mathematical optimization models.
• Design, develop, and implement algorithms and heuristics for finding optimal or near-optimal solutions at scale.
• Work on defining objective functions, constraint sets, and conducting sensitivity analysis to ensure model robustness.
• Collaborate with data engineering teams to structure input data for optimization models.
• Contribute to low-latency production systems for real-time optimization and decision making.
• Rigorously validate model outputs against real-world operations and continuously improve solution quality.
• Analyze operational trade-offs and build simulation frameworks to evaluate the impact of optimization strategies.
• Partner with product and operations teams to translate business needs into mathematical optimization solutions.

Are you who we're searching for

We are looking for a highly motivated Data Scientist I to join our team, focusing on Supply Chain Optimization. This role involves applying mathematical rigor and advanced algorithmic techniques to solve complex, large-scale business problems across logistics, supply chain, and operations. You will be responsible for defining, developing, and deploying high-impact optimization models (e.g., Linear Programming, Mixed-Integer Programming) and leveraging heuristics and graph algorithms to find optimal or near-optimal solutions under strict latency and scale constraints. You will collaborate closely with Data Engineers, MLOps Engineers, Product, and Operations teams to integrate OR solutions into our production systems, ensuring both mathematical correctness and operational efficiency. The ideal candidate is passionate about solving real-world problems using mathematical modeling, has a strong foundation in algorithm complexity and data structures, and is excited to work on high-impact systems where solution quality directly drives business growth and customer experience.

Technical Skills (Must Have)

• Strong programming skills in Python and strong SQL skills for data extraction, transformation, and analysis
• Solid understanding of optimization techniques, including: Linear Programming (LP) and Mixed-Integer Programming (MIP), and metaheuristics.
• Hands-on experience with optimization solvers and libraries (e.g., PuLP, OR Tools, Gurobi, CPLEX).
• Knowledge of algorithm complexity, Data structures, and Graph algorithms.
• Demonstrated mathematical rigour in problem formulation and solution design.
• Understanding of performance bottlenecks and strategies for optimizing algorithm speed.

Core Competencies

• Strong analytical and problem-solving skills with attention to detail
• Ability to break down complex real-world problems into structured mathematical optimization models (e.g., LP, MIP).
• Demonstrated mathematical rigour in problem formulation and solution design.
• Strong debugging and model validation skills, ensuring mathematical correctness and operational efficiency.
• Ability to work in high-scale, fast-paced environments with evolving data and tight latency constraints.
• Clear communication and collaboration with cross-functional teams, including Product and Operations.
• Ownership mindset with a focus on impact and continuous improvement.

Preferred Experience

• Experience in modeling and solving large-scale optimization problems in areas like routing, scheduling, or network design.
• Exposure to designing and implementing algorithms, heuristics, and metaheuristics for large-scale, near-real-time problem solving.
• Exposure to or practical experience with Discrete Event System Simulation (DESS) for modeling and analyzing complex operational processes and system trade-offs.
• Experience with deploying optimization models into low-latency production systems.
• Practical experience with building simulation frameworks to evaluate operational trade-offs and impact.
• Familiarity with big data processing tools like PySpark and cloud data platforms.
• Knowledge of handling high-throughput, low-latency systems.

• 0–2 years of experience in Data Science, Machine Learning, or related roles
• Freshers with strong internships / academic projects in ML, data analysis, or large-scale data processing are encouraged to apply
• Hands-on exposure to building and evaluating ML models
• Experience working with real-world datasets, feature engineering, and model evaluation is a plus

Qualification

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative field
• Strong foundation in probability, statistics, linear algebra, and machine learning fundamentals
• Demonstrated academic or project experience in applied machine learning and data-driven problem solving

Sounds like we’re talking about you? Please add your application to our cart!

Equal Opportunity Statement: Zepto is an equal opportunity employer and is committed to building an inclusive workplace. All qualified applicants will receive consideration without regard to race, color, religion, gender, sexual orientation, national origin, or disability status.