Job description 

Roles and Responsibilities:

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

Qualifications & Experience:

• 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 PhD 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 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.