Senior Data Scientist

Myntra is hiring for the role of Senior data scientist!

Responsibilities of the Candidate:

• Develop data science and machine learning models for Myntra Storefront, Supply Chain, and other areas
• Be conversant with machine learning life cycles, model deployments, etc.
• Understand and practice of machine learning and expertise in one or more of the topics, such as Time Series, Forecasting, NLP, Computer Vision, and Optimisation.
• Collaborate with Product and Business to formulate the problem into a Machine Learning model.
• Connect with Platforms and Engineering teams to make sure the predictive models built are deployed and integrated into the systems.
• Work with the Data Platforms teams for understanding, and collecting the data.

Requirements:

• Knowledge on data structures, algorithms and efficient processing of large datasets.
• Well-versed with Python.
• Good to have publications.
• 2-4 years of experience with MTech, MS by Research or Ph.D. in Computer Science/Electrical Engineering, or post-graduate degree in Statistics, Operations Research, or Mathematics
• Experience in developing efficient Time Series and forecasting solutions. 
• Good to have some experience with large-scale nonlinear & integer programming algorithms - hands-on with optimization solvers (CPLEX, Gurobi, COIN-OR, etc.) 
• Good to have skills in general Machine Learning and Deep Learning such as
• Natural Language Processing (NLP): Skills in NLP to develop models that understand and generate human language.
• Computer Vision: Knowledge of computer vision techniques to interpret images and videos, including object identification and classification.
• DevOps: Familiarity with DevOps principles and practices for deploying and managing machine learning models in production environments.
• LLM and GenAI Models: Understanding of Large Language Models (LLM) and Generative AI (GenAI) models, including prompt engineering, model evaluation, optimization, and deployment.
• Domain Knowledge: Expertise in a specific industry or field, enabling a better understanding of data and business needs.
• Ethical Data Science: Awareness of ethical considerations in data science, including privacy, bias, and fairness.
• Collaboration: Strong communication and teamwork skills for effective collaboration with cross-functional teams, including engineers, product managers, and designers.