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  • Data Scientist and 1 Other Post in Union Bank of India via Direct Recruitment

    Event Status : Advertisement Cancelled

Timeline

Important Dates

Application Closing Date
03/09/2023
Application Opening Date
02/08/2023

Other Important Information

Appointment Type
Direct Recruitment
Application Submission Method
Online
Age Limit
21-35
Qualification Required
Graduate, Postgraduate
Total Vacancies
4
Application Fee
Yes
Location of Posting/Admission
Mumbai, Maharashtra, India, 400070
Organisation Type
Non-Educational Institution
Place of Posting/Admission
Mumbai, Maharashtra, India
Website
https://www.unionbankofindia.co.in/english/home.aspx
Post Type
Contractual
Work Experience
Yes
Age Relaxation Type
SC/ST, Other Backward Class, Person with Benchmark Disabilities
Interview
Yes
Application Link
https://www.unionbankofindia.co.in/

Note: This information is common for all posts. For details on specific posts, refer to the official notification.

Posts Released

1. Data Scientist
2. Machine Learning Engineer

Important Updates

Refer to the official notification for more details.

Application Summary

Union Bank of India has released notifications for the Data Scientist and Machine Learning Engineer posts. Interested candidates can apply from 02/08/2023 to 03/09/2023. Download the official notification for details on eligibility, post information, job procedure, pay scale, and more.

Union Bank of India invites applications for the following posts via direct recruitment:

Post Name: Data Scientist

Essential Qualification:

  1. M.Sc. in Statistics/ B.Tech/MCA

  2. Minimum 60% marks in the applicable qualification from above

Desirable Qualification:

  1. Ability to work independently, manage small engagements or parts of large engagements

  2. Strong problem solving and troubleshooting skills with the ability to exercise mature judgment

Essential Work Experience: The candidate should have at least 5+ years of hands-on experience in mathematical modelling, machine learning, Advanced Analytics, AI and ML Use Cases with at least 3 years of technical experience & functional knowledge in Banking Industry

Desirable Experience:

  1. Should be strong in probability and foundations of machine learning

  2. Advanced working knowledge of Python/R or other languages/technologies for performing complex data modeling and analysis

  3. Breadth of knowledge across statistical methods, machine learning models, deep learning, natural language processing, conceptual modeling, predictive modeling, hypothesis testing to solve data problems

  4. Expert level knowledge in frameworks/libraries such as NumPy, OpenCV, Pandas, Tensor Flow, Keras, Scikit-learn, NLTK, etc.

  5. Good knowledge of data visualization, SQL, ETL, and data management concepts

  6. Strong analytical thinking, and problem-solving skills

  7. Strong business acumen to understand context of the research situation and identify data analytics opportunities to differentiate analysis.

  8. Guide analytics process by framing hypotheses and stating research problem to accurately reflect the research situation

Post Name: Machine Learning Engineer

Essential Qualification:

  1. B. Tech/MCA

  2. Minimum 60% marks in the applicable qualification from above

Desirable Qualification:

  1. Strong problem solving and troubleshooting skills with the ability to exercise mature judgment

  2. Ability to work independently, manage small engagements or parts of large engagements

Essential Work Experience: At least 5+ years of hands-on data science experience using Python, R for data analytics, visualization, statistical programming, data mining and NLP for problem solving and minimum 3 yearsтАЩ experience in Banking Industry

Desirable Experience:

  1. Understanding of data structures, data modeling and software architecture

  2. Ability to write robust code in Python, Java and R

  3. Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)

  4. Machine learning, recommendation systems, pattern recognition, data mining and artificial intelligence

  5. Translating insights into business recommendations

  6. Scripting languages, including Perl, Python, PHP, and shell scripts

  7. SQL, ETL, and data modeling

  8. Deep Learning frameworks like MXNet, Caffe 2, Tensorflow, Theano, CNTK, Yolo, Pytorch and Keras to help our customers build DL models.

  9. Statistics methods, including forecasting, time series, hypothesis testing, classification, clustering or regression analysis, and statistical/mathematical software (R)

  10. Strong business acumen to understand context of the research situation and identify data analytics opportunities to differentiate analysis.

For more details related to eligibility criteria, fee, pattern, annexure, place of posting etc. refer to the attachments below.