Data Scientist
Myntra
Bengaluru, Karnataka, India
About Team Myntra Data Science team delivers a large number of data science solutions for the company which are deployed at various customer touch points every quarter. The models create significant revenue and customer experience impact. The models involve real-time, near-real-time and offline solutions with varying latency requirements. The models are built using massive datasets. You will have the opportunity to be part of a rapidly growing organization and gain exposure to all the parts of a comprehensive ecommerce platform. You’ll also get to learn the intricacies of building models that serve millions of requests per second at sub second latency. The team takes pride in deploying solutions that not only leverage state of the art machine learning models like graph neural networks, diffusion models, transformers, representation learning, optimization methods and bayesian modeling but also contribute to research literature with multiple peer-reviewed research papers. 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 practise of machine learning and expertise in one or more of the topics, such as, 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 or equivalent programming language. People with MTech, MS by Research or PhD in Computer Science/Electrical Engineering, or post graduate degree in Statistics, Operations Research, or Mathematics are preferred. Having authored publications is plus 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 Other 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.
