Operation Research Scientist

About Team

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 utilize state-of-the-art machine learning techniquessuch as graph neural networks, diffusion models, transformers, representation learning, optimization methods, and Bayesian modelingbut also contribute to the research community withmultiple peer-reviewed publications.

Roles and Responsibilities

• Design, develop, and deploy advanced machine learning models and algorithms for Forecasting, Operations Research, and Time Series applications.
• Build and implement scalable solutions for supply chain optimization, demand forecasting, pricing, and trend prediction.
• Develop efficient forecasting models leveraging traditional and deep learning-based time series analysis techniques.
• 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

• 1-3 years of experience with a Masters degree or 2-4 years of experience with a Bachelors 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).
• Knowledge of ML orchestration tools such as Airflow, Kubeflow, and MLflow.
• Exposure to NLP and Computer Vision applications in an e-commerce setting.
• Understanding of ethical considerations in AI, including bias, fairness, and privacy.