Job Information
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.
We take pride in deploying solutions that not only utilise state-of-the-art machine learning techniques—such as Hierarchical demand models, Deep choice neural network models, explainable substitutability models using knowledge graphs and choice theory, GNNs for linkage/substitutability, optimization methods, Bayesian modeling, besides other diffusion models, transformers, representation learning etc —but also contribute to the research community with multiple peer-reviewed publications.
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.
Nice to Have
- Experience with Generative AI and Large Language Models (LLMs)
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