Data Scientist Associate

2 weeks ago


Bengaluru, Karnataka, India JPMorgan Chase Full time ₹ 1,20,000 - ₹ 1,80,000 per year

You thrive on diversity and creativity, and we welcome individuals who share our vision of making a lasting impact. Your unique combination of design thinking and experience will help us achieve new heights.


  As a Data Scientist Associate at JPMorgan Chase within the Asset & Wealth Management, you are part of an agile team that works to enhance, design, and deliver the data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. As an emerging member of a data engineering team, you execute data solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role.  

Job responsibilities

  • Collaborates with all of JPMorgan's lines of business and functions to delivery software solutions. 
  • Experiments, develop and productionize high quality machine learning models, services and platforms to make huge technology and business impact. 
  • Designs and implement highly scalable and reliable data processing pipelines and perform analysis and insights to drive and optimize business result. 
  • Adds to team culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

  • Formal training or certification on Data Science concepts and 2+ years applied experience
  • Solid programming skills with Python/Java or other equivalent languages. 
  • Deep knowledge in Data structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, Statistics. 
  • Expert in at least one of the following areas: Natural Language Processing, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis. 
  • Knowledge of machine learning frameworks: Tensorflow/Pytorch 
  • Knowledge of prompt engineering. Experience in ETL data pipelines both batch and real-time data processing, Data warehousing, NoSQL DB, Elastic. 
  • Cloud Technologies: AWS/GCP/Azure, Kubernetes 
   
 

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