Job description

Key Responsibilities

  • Data Science :
  • Build ML/AI models leveraging a strong understanding of Machine Learning principles including standard algorithms for Regression and Classification, Deep Learning constructs (RNN, CNN, RBMs, Auto Encoders, GANs) and AI systems such as Voice to Text, NLP/NLU and Recommender systems
  • Build recommender systems around agent Collections prioritization, product recommendations, and personalization engines
  • Build sophisticated pricing engines based on AI powered product evaluation tools
  • Build cross-sell/up-sell recommender systems using deep learning frameworks, and with sparse data
  • Cloud Big Data:
  • Work on Cloud Infrastructure (Azure, AWS) to provision data to ML models, build ML systems on deploy them at scale
  • Build ML systems using Spark libraries such as ML Lib, Spark SQL and be able to deploy them on clusters/machines, both on Cloud and on-Prem
  • Build Production level Models @ scale
  • Design and implement the machine learning lifecycle at scale, from building the data infrastructure to train/test Machine learning models to their production environments.
  • Management of production ML workflows ensuring automated CI/CD capabilities are built into the work flow

Job Requirements

  • Ability Work closely with Data Analysts, Data Scientists and Business Analysts
  • Comfortable to work in cross-functional team and collaborate with peers during the project lifecycle


BE/B.Tech/BS/MS/PhD in Computer Science or a related field preferably from a Premier institute ( Tier 1 IITs, BITS and Top NITs, Ivy League US Schools)


  • 8+ years of work experience as a Data Scientist with at least 4-5 year designing and implementing ML platforms for enterprise-grade ML use cases
  • Start-up experience is a plus


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