Senior Data Scientist - Forecasting

About The Company Who are we? Myntra is India’s leading fashion and lifestyle platform, where technology meets creativity. As pioneers in fashion e-commerce, we’ve always believed in disrupting the ordinary.

We thrive on a shared passion for fashion, a drive to innovate to lead, and an environment that empowers each one of us to pave our own way. We’re bold in our thinking, agile in our execution, and collaborative in spirit.

Here, we create MAGIC by inspiring vibrant and joyous self-expression and expanding fashion possibilities for India, while staying true to what we believe in.

We believe in taking bold bets and changing the fashion landscape of India. We are a company that is constantly evolving into newer and better forms and we look for people who are ready to evolve with us.

From our humble beginnings as a customization company in 2007 to being technology and fashion pioneers today, Myntra is going places and we want you to take part in this journey with us.

Working at Myntra is challenging but fun - we are a young and dynamic team, firm believers in meritocracy, believe in equal opportunity, encourage intellectual curiosity and empower our teams with the right tools, space, and opportunities.

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 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).
• 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.

Exceptional candidates are encouraged to apply, even if they don’t meet every listed qualification. We value potential and a strong willingness to learn.

Required Skills forecasting, optimization, pyspark, machine learning

Required Education PG