KPMG India Recruitment 2022 for KGS – Data Scientist – Assistant Manager in Bangalore

  • Full Time
  • Private Jobs
  • Bangalore
  • Posted 4 months ago

KPMG India

LAST DATE FOR APPLY: NOT SPECIFIED

Naukri in KPMG India 2022

 

Naukri in KPMG India, published in 15-02-2022,this company is releated to Telecom sector. Which needs job persons or employees who are eligible to apply for the

KPMG India company recruitment 2022.So applicants are invited application for the recruitment to the post of KGS – Data Scientist – Assistant Manager

  .So any interested applicant kindly read this job post carefully in details bellow and take the necessary action to getting the jobs.

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.

POST NAME:

KGS – Data Scientist – Assistant Manager

JOB TYPE:

Full time

JOB LOCATION:

Bangalore, Karnataka, India

SALARY:

Not Specified

 

EDUCATION & EXPERIENCE:

Candidate should have Masters in Computer Science / Machine learning / Statistics / Mathematics with 4+ years of experience A strong level of proficiency in python  programming Working knowledge of deep learning frameworks like Pytorch or tensorflow Proficient with NLP techniques like RNN, LSTM, Attention based models Good understanding of how to apply predictive and machine learning techniques like logistic regression, random forest, GBM, Neural Nets, SVM etc is required Good understanding of databases (SQL) from a perspective of how to write efficient queries and pull data from them Experience of putting ML models into production Experience in any one of the cloud platforms like (Azure, GCP, AWS etc) Working knowledge of any version control tool (github, bitbucket) Working knowledge of distributed computing such as Hadoop, Spark, Databricks etc

 

JOB DESCRIPTION:

Comprehend business issue and the accessible information and distinguish what factual or AI/profound learning methods can be applied to address a business question.
Fabricate Statistical Models/ML/DL models, train and test them and drive towards ideal degree of execution
Get what information is accessible and where and how to arrange it.
Productionalization of models and computerize criticism circles

 

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