Machine Learning Engineer – Forecasting and Optimization

Job Description

Data Scientist – OR | Myntra

The Tone:
This is a full-time role at Myntra, located in Bangalore, India. Myntra is a leading e-commerce platform focused on fashion and lifestyle. This position is vital for advancing Myntra’s operational efficiency and customer satisfaction through the application of sophisticated machine learning and optimization techniques. The role directly contributes to enhancing critical business areas such as supply chain management, demand prediction, and pricing strategies.

The TL;DR
• Role: Full Time
• Type: Full-time
• Location: In-person, India (Karnataka) – Bangalore

• Team: Cross-functional collaboration with Product, Engineering, Business, and Data Platforms teams
• Mission: Lead the design, development, and deployment of advanced ML and OR models to optimize Myntra’s supply chain, forecasting, and pricing strategies.
• Tech Stack: Python, TensorFlow, PyTorch, Scikit-learn, CPLEX, Gurobi, COIN-OR, AWS, Google Cloud, Airflow, Kubeflow, MLflow

What You’ll Actually Do
• Design and deploy advanced machine learning models and algorithms for forecasting, operations research, and time series applications.
• Build and implement scalable solutions to optimize supply chain, demand forecasting, pricing, and trend prediction across the business.
• Develop and enhance efficient forecasting models utilizing both traditional and deep learning-based time series analysis techniques.
• Apply and leverage optimization techniques for large-scale nonlinear and integer programming problems, including hands-on use of solvers.
• Collaborate with Product, Engineering, and Business teams to integrate ML solutions and maintain robust machine learning pipelines.

The Must-Haves
• Background: Master’s degree with 1-3 years of experience, or a Bachelor’s degree with 2-4 years of experience, in Statistics, Operations Research, Mathematics, Computer Science, or a related quantitative field.
• Experience: Proven experience in developing and deploying forecasting and time series models, coupled with hands-on experience using optimization solvers and algorithms for supply chain and logistics challenges.
• Skills: Proficiency in Python for data science and ML, familiarity with frameworks like TensorFlow, PyTorch, and Scikit-learn, and strong problem-solving skills applying OR techniques to real-world problems.
• Bonus: Research publications in Machine Learning, Forecasting, or Operations Research, familiarity with cloud computing services (AWS, Google Cloud) and distributed systems, and knowledge of ML orchestration tools such as Airflow, Kubeflow, and MLflow.