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
Important Updates
Refer to the official notification for more details.
Application Summary
Union Bank of India invites applications for the following posts via direct recruitment:
Post Name: Data Scientist
Essential Qualification:
M.Sc. in Statistics/ B.Tech/MCA
Minimum 60% marks in the applicable qualification from above
Desirable Qualification:
Ability to work independently, manage small engagements or parts of large engagements
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:
Should be strong in probability and foundations of machine learning
Advanced working knowledge of Python/R or other languages/technologies for performing complex data modeling and analysis
Breadth of knowledge across statistical methods, machine learning models, deep learning, natural language processing, conceptual modeling, predictive modeling, hypothesis testing to solve data problems
Expert level knowledge in frameworks/libraries such as NumPy, OpenCV, Pandas, Tensor Flow, Keras, Scikit-learn, NLTK, etc.
Good knowledge of data visualization, SQL, ETL, and data management concepts
Strong analytical thinking, and problem-solving skills
Strong business acumen to understand context of the research situation and identify data analytics opportunities to differentiate analysis.
Guide analytics process by framing hypotheses and stating research problem to accurately reflect the research situation
Post Name: Machine Learning Engineer
Essential Qualification:
B. Tech/MCA
Minimum 60% marks in the applicable qualification from above
Desirable Qualification:
Strong problem solving and troubleshooting skills with the ability to exercise mature judgment
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:
Understanding of data structures, data modeling and software architecture
Ability to write robust code in Python, Java and R
Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)
Machine learning, recommendation systems, pattern recognition, data mining and artificial intelligence
Translating insights into business recommendations
Scripting languages, including Perl, Python, PHP, and shell scripts
SQL, ETL, and data modeling
Deep Learning frameworks like MXNet, Caffe 2, Tensorflow, Theano, CNTK, Yolo, Pytorch and Keras to help our customers build DL models.
Statistics methods, including forecasting, time series, hypothesis testing, classification, clustering or regression analysis, and statistical/mathematical software (R)
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.