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Day 4
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From 11,783 similar postings that came down. Coming down is not always a hire.
The Risk Analytics team is responsible for the estimation of risk parameters (PD, LGD & CCF) for internal & regulatory purpose, Ind AS ECL implementation and execution.
� Should have strong analytical & problem solving skill � Should have strong working knowledge of SAS, R, Python and data mining tools � Be able to influence stakeholders on data driven strategies
The Risk department ensures that the Bank�s risk is managed through a risk management architecture as well as through policies and processes approved by the Board of Directors encompassing independent identification, measurement and management of risks across the various businesses of the Bank.
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Actively hiringFirst seen by us 4 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 4
Early. Similar jobs usually come down between day 8 and day 60.
From 11,783 similar postings that came down. Coming down is not always a hire.
47 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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Yes. We’ve followed 11 other Risk:Risk Analytics Team jobs there since November 2026. All 11 are still up.
Large employers often post one title for several teams, so these can be separate openings.
New Data Scientist postings at the employers we follow are down 4% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
� Responsible for tracking portfolio trends and hot spots
� Responsible for tracking early warning signals, root-cause analysis, covering Business Segments, Sector and Groups
� Provide timely and actionable insights to the top management and business heads
� Provide key risk inputs to the capital computation process
� Track RAROC for customer, product, portfolio (segment, industry)
� Estimation and validation of IRB (Capital Computation Approach)
� Manage IRB Capital run and reporting process.
� Responsible for the development of Credit Risk models and revamp of new models��������������������������
QualificationsOptimal qualification for success on the job is:
� Post graduate with specialization in Quant and statistics viz. Masters in statistics, MBA, M Tech with relevant risk analytical exposure (Risk, Collections and Fraud)
� Hands on experience in Advanced & Predictive analytics, Decision Tree, Segmentation analysis and Cluster analysis using analytical and statistical procedures
Role Proficiencies:� Should have strong analytical & problem solving skill
� Should have strong working knowledge of SAS, R, Python and data mining tools
� Be able to influence stakeholders on data driven strategies
� Should have good communication, presentation and inter-personal skills
� Should have high level of motivation and be a fast learner
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