Manager,WCR Analytics

HSBC; Bengaluru; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

HSBC is seeking an experienced Manager, Wholesale Credit Risk Analytics to lead quantitative analytics across global portfolios from Bengaluru. You will apply statistical and machine learning methods to derive actionable insights and partner with IT/Data Eng to map deployment roadmaps, delivering high-impact projects with business partners across regions.

The role requires at least 5 years of relevant experience, a Masters in a quantitative field, and strong Python and Gen AI proficiency.

Qualifications

• At least 5 years of experience using statistical concepts or ML to solve business problems.
• Master’s degree in a quantitative field (Math/Stats/Economics/Engineering/CS/Management).
• Proficiency in Python and Gen AI tools.

Responsibilities

• Apply analytical methods to get actionable insights from HSBC's data sources.
• Partner with IT/Data Engineering to create deployment roadmap.
• Independently manage analytics projects with business partners across regions.
• Support Central Model Monitoring for IRB models across Wholesale portfolios.
• Engage with senior stakeholders across Wholesale Risk.
• Adhere to internal controls and regulatory requirements.

Skills

Python

Gen AI tools

Statistical concepts

Machine learning

Stakeholder management

Education

Master's degree in Mathematics/Statistics/Economics/Engineering/CS/Management

Job description

Some careers shine brighter than others. If you’re looking for a career that will help you stand out, join HSBC and fulfil your potential. Whether you want a career that could take you to the top, or simply take you in an exciting new direction, HSBC offers opportunities, support and rewards that will take you further.

HSBC is one of the largest banking and financial services organisations in the world, with operations in 64 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people to fulfil their hopes and realise their ambitions.

We are currently seeking an experienced professional to join our team in the role of Manager, Wholesale Credit Risk Analytics

In This Role, You Will

• Decision Sciences job family is structured to address business problems with quantitative solutions like building of predictive algorithms / forecasting / scenario simulations etc. Members of this Job Family are differentiated by their capability of converting a business problem into a quantitative construct, solve it with available statistical / mathematical methods (following the right rigour), engage with IT to implement and finally interpret the model outcomes in business language. The range of business problems may cover areas of business growth, improving customer experience, limiting risk exposure, capital quantification, enhancing internal business processes etc. They are required to, as necessary, embed agile & exploratory practices into their approach, justify the choice of appropriate methods to various internal and external reviewers. This talent group is expected to keep themselves apprised of latest developments and industry practices around emerging methodologies, techniques etc. and bring those in-house by applying them for better outcomes.
• Apply relevant analytical methods / algorithms to get actionable insights from HSBC's internal (both structured and unstructured) and external data sources
• Partner with IT / Data Engineering teams to create deployment roadmap
• Independently manage delivery of analytics projects by working with business partners across regions / geographies
• This role will be responsible for supporting Central Model Monitoring in the following capacities:
• Perform Model monitoring activities related to IRB models for all Wholesale portfolios across the Globe.
• The individual is also required to work on key projects within Model Monitoring function and drive changes as on when required.
• You would need to Interact with senior stakeholders across Wholesale Risk.
• The jobholder will continually reassess the operational risks associated with the role and inherent in the business, taking account of changing economic or market conditions, legal and regulatory requirements, operating procedures and practices, management restructurings, and the impact of new technology.
• The jobholder will also adhere to and be able to demonstrate adherence to internal controls. This will be achieved by adherence to all relevant procedures, keeping appropriate records and, where appropriate, by the timely implementation of internal and external audit points, including issues raised by external regulators.

To Be Successful You Will

• At least 5 Years of relevant work experience of using statistical concepts and (or) machine learning models to solve complex business problems. Preferably, at least 3 years of work experience related to Credit Risk in Financial domain
• At least master’s degree in mathematics, Statistics, Economics, Engineering, Computer Science, Management or other quantitative fields of study
• Proficiency in Python and Gen AI tools are desired
• Business problem solving skills is essential
• Strong business acumen with out-of-the box thinking to drive improved business performance
• Strong stakeholder management skills and seamless delivery of analytics initiatives across markets
• Excellent written and verbal communication skills. Ability to develop and effectively communicate complex concepts and ideas
• Strong knowledge and understanding of financial-services/ banking-operations

You’ll achieve more at HSBC

hsbc.com/careers

HSBC is an equal opportunity employer committed to building a culture where all employees are valued, respected and opinions count. We take pride in providing a workplace that fosters continuous professional development, flexible working and, opportunities to grow within an inclusive and diverse environment. We encourage applications from all suitably qualified persons irrespective of, but not limited to, their gender or genetic information, sexual orientation, ethnicity, religion, social status, medical care leave requirements, political affiliation, people with disabilities, color, national origin, veteran status, etc., We consider all applications based on merit and suitability to the role.

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