Risk Analytics and Modelling

-Job description

**Role purpose**

Global Analytics Center (GAC), is a hub of advanced analytics competency, providing high-end analytics services across global businesses and global functions. Set-up in India in 2004, GAC has matured into a shared Centre of Excellence comprising 2000+ professionals with offices in Bangalore, Kolkata, Guangzhou and Krakow. The work done in GAC forms a vital input towards for strategic planning by the senior management for businesses and enables effective decision making along with addressing unforeseen challenges.

GAC is an innovative community leveraging the best of data and analytics capabilities to enable smarter decisions and drive profitable growth. Rightly positioned in the two major intellectual hubs of India, Poland and China, it attracts a rich mix of resources across business consulting, data analysts, decisions scientists and advance analytics professionals. Being in these locations also enables HSBC to leverage talent from the rich academic and start-up ecosystem to keep up to date with the latest in the industry.

Today, the GAC team generates value across the group through a wide variety of data and analytic solutions and related business consulting. GAC has become a one-stop shop for the group’s analytic needs leading the integration of analytics and data-driven decisions not only in traditional areas such as Risk, Retail, Wholesale, Private & Commercial Banking but also in new domains such as Regulatory, Operations, Procurement, Human Resources, and Financial Crime Risk. It provides support to various business groups and the job involves data analysis, model and strategy development & implementation, Business Intelligence, reporting and data management

**Principal Accountabilities and Responsibilities**

Responsible for the entire lifecycle of model - collecting data, building and implementing models, and performance tracking. Develop and monitor wholesale credit risk analytic measurements/tools/models for specific products or portfolios as assigned. Ensure models are conceptually sound and meet all regulatory requirements based on its use case (e.g., Basel II, IFRS 9/CECL, Stress Testing (CCAR)). Support key decision-making processes including, not limited to stress testing, capital allocation, strategic decision-making, and performance measurement. Function as an individual contributor of technical expertise for the area.
- 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.
- The jobholder will implement the Group compliance policy by containing compliance risk in liaison with Global Head of Compliance, Global Compliance Officer, Area Compliance Officer or Local Compliance Officer. The term ‘compliance’ embraces all relevant financial services laws, rules and codes with which the business has to comply.
- This will be achieved by adhering to all relevant processes/procedures and by liaising with Compliance department about new business initiatives at the earliest opportunity. Also and when applicable, by ensuring adequate resources are in place and training is provided, fostering a compliance culture and optimising relations with regulators
Requirements
- 5+ years of experience of developing predictive models leveraging statistical and (or) machine learning methods to solve complex business problems, credit risk and stress testing modelling experience is a plus.
- At least Master's degree in a quantitative discipline, e.g. Mathematics, Statistics, Economics, Computer Science, Data Science.
- Proficiency in SAS / R, Python, and MS Office tools like Excel & PowerPoint, proficient in git version control.
- Extensive experience with Machine Learning APIs and computational packages (e.g. Scikit-Learn, Numpy, SciPy, Pandas, statsmodels)
- Familiarity with data table operations (SQL, BigQuery, etc)
- Should be able to work both individually and collaboratively in teams.
- Must be proficient in English as the jobholder will work closely with the team in the United States. Strong communication and presentation skills (both verbal and written) and ability to develop and effectively communicate complex technical concepts and ideas to non-technical/analytica recipient

**Others**
- Good understanding of the business activities for a large global banking group with diverse operations from wealth management, commercial banking, global banking, investments, private banking and insurance.
- M