Data Scientist

Bengaluru

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

  • Design, develop and deploy machine learning models,algorithms and systems to solve complex business problems for Myntra Recsys, Search, Vision, SCM, Pricing, Forecasting, Trend and Virality prediction, Gen AI and other areas
  • Theoretical understanding and practise of machine learning and expertise in one or more of the topics, such as, NLP, Computer Vision, recommender systems and Optimisation. 
  • Implement robust and reliable software solutions for model deployment.
  • Support the team in maintaining machine learning pipelines, contributing to tasks like data cleaning, feature extraction and basic model training.
  • Participate in monitoring the performance of machine learning models, gaining experience in using statistical methods for evaluation.
  • Working with the Data Platforms teams for understanding and collecting the data.
  • Conduct performance testing, troubleshooting and tuning as required.
  • Stay current with the latest research and technology and communicate your knowledge throughout the enterprise.

Qualifications & Experience

  • Master’s/PhD in Computer Science, Mathematics, Statistics/related fields ‘or’ 1+ years of relevant industry experience with a Bachelor’s degree.
  • Proficiency in Python or one other high-level programming language.
  • Theoretical understanding of statistical models such as regression, clustering and ML algorithms such as decision trees, neural networks, etc.
  • Strong written and verbal communication skills
  • Intellectual curiosity and enthusiastic about continuous learning
  • Experience developing machine learning models in Python,  or equivalent programming language.
  • Basic familiarity with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn.
  • Introductory understanding of statistics as it applies to machine learning.
  • Ability to manage and prioritize your workload and support his/her manager.
  • Experience with SQL and/or NoSQL databases.
  • If you are an exceptional candidate, write in. We are happy to hire you even if you don't have the certified qualifications.

Nice to Have:

  • Publications or presentations in recognized Machine Learning and Data Science journals/conferences.
  • Experience with ML orchestration tools (Airflow, Kubeflow or MLFlow)
  • Exposure to GenAI models.

 

Apply now Apply later
  • Share this job via
  • or

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Airflow Bayesian Clustering Computer Science Computer Vision CX Diffusion models E-commerce Generative AI Kubeflow Machine Learning Mathematics MLFlow ML models Model deployment Model training NLP NoSQL PhD Pipelines Python PyTorch Recommender systems Research Scikit-learn SQL Statistics TensorFlow Testing Transformers

Perks/benefits: Conferences

Region: Asia/Pacific
Country: India
Job stats:  37  8  1
Category: Data Science Jobs

More jobs like this

Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.