The Myntra Data Science team is at the forefront of innovation, delivering cutting-edge solutions that drive significant revenue and enhance customer experiences across various touchpoints. Every quarter, our models impact millions of customers, leveraging real-time, near-real-time, and offline solutions with diverse latency requirements. These models are built on massive datasets, allowing for deep learning and growth opportunities within a rapidly expanding organization. By joining our team, you’ll gain hands‑on experience with an extensive e‑commerce platform, learning to develop models that handle millions of requests per second with sub‑second latency.
Roles and Responsibilities
- Design, develop, and deploy advanced machine learning models and algorithms for Forecasting, Operations Research, and Time Series applications, choice modeling, Hierarchical mixture modeling.
- Build and implement scalable solutions for supply chain optimization, demand forecasting, pricing, and trend prediction, assortment placement optimisation.
- Develop efficient forecasting models leveraging ML/DL based time series analysis techniques with hierarchical estimation methods , and simulations.
- Utilize optimization techniques for large-scale nonlinear and integer programming problems.
- Hands‑on experience with optimization solvers like CPLEX, Gurobi, COIN-OR, or similar tools.
- Collaborate with Product, Engineering, and Business teams to understand challenges and integrate ML solutions effectively.
- Maintain and optimize machine learning pipelines, including data cleaning, feature extraction, and model training.
- Implement CI/CD pipelines for automated testing, deployment, and integration of machine learning models.
- Work closely with the Data Platforms team to collect, process, and analyze data crucial for model development.
- Stay up to date with the latest advancements in machine learning, forecasting, and optimization techniques, sharing insights with the team.
Qualifications & Experience
- 2-4 years of experience with a Master’s degree or 3-4.5 years of experience with a Bachelor’s degree in Statistics, Operations Research, Mathematics, Computer Science, or a related field.
- Strong foundation in data structures, algorithms, and efficient processing of large datasets.
- Proficiency in Python for data science and machine learning applications.
- Experience in developing and deploying forecasting and time series models.
- Knowledge of ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.
- Hands‑on experience with optimization solvers and algorithms for supply chain and logistics problems.
- Strong problem‑solving skills with a focus on applying OR techniques to real‑world business challenges.
- Good to have research publications in Machine Learning, Forecasting, or Operations Research.
- Familiarity with cloud computing services (AWS, Google Cloud) and distributed systems.
- Strong communication skills with the ability to work independently and collaboratively in a team environment.