Data Scientist- Business Risk

Some careers shine brighter than others.

If youre 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 ofData Scientist-Business Risk

In this role you will:

• Act as a fraud analytics SME and trusted advisor for CIB Business Risk supporting Fraud Risk Management within the Merchant Card Acquiring business across one or more regions.
• Partner with Acquiring business teams Operations Technology Product Compliance and Financial Crime Risk to drive data-led decisions that reduce fraud losses while protecting merchant and customer experience.
• Maintain a strong understanding of the merchant acquiring lifecycle (onboarding underwriting transaction processing settlement and disputes/chargebacks) and the key fraud risks and control points across each stage.
• Develop and support analytics strategies aligned to business priorities including improved detection effectiveness reduced false positives and stronger control reusable and scalable analytical assets (typologies features rules model components and monitoring packs) that can be deployed consistently across markets and merchant segments.
• Communicate complex analytical findings in a clear executive-ready format enabling timely decisions and effective governance while consistently upholding HSBC Core Values.
• Key focus areas: Merchant Acquiring fraud and implement fraud typologies across the merchant lifecycle including:Onboarding and underwriting (e.g. suspicious applications high-risk profiles).Early-life monitoring (e.g. rapid spikes in activity abnormal refunds/voids)
• Portfolio monitoring (e.g. behavioural drift emerging patterns peer outliers).Build and operationalise detection approaches such as:Anomaly detection for volume value velocity geography refund ratios and chargeback rates.
• Rules and scorecards to support near-real-time monitoring and analytics to identify linked merchants and suspicious relationship and peer benchmarking by MCC channel (e-commerce vs card-present) region and merchant size.
• Support priority fraud themes including CNP fraud patterns refund/chargeback abuse and indicators of compromised merchants ensuring solutions are practical for operational technology and delivery expectations
• Deliver robust ETL and data pipeline capabilities across acquiring transaction feeds merchant master data onboarding data and disputes/chargebacks ensuring strong data quality and cloud analytics platforms such as GCP AWS (including Redshift) and/or Azure to support scalable delivery and engagement and collaboration.

To be successful you will:

• Degree-level qualification (or equivalent relevant experience) in Data Science Computer Science Statistics Mathematics Finance or another quantitative discipline.
• 6 years relevant experience ideally within banking or the financial services grounding in advanced analytical methods such as regression predictive modelling data mining and machine learning with a structured and creative approach to problem solving.
• Proficiency in Python SQL (or similar analytical programming languages) Alteryx with experience in one or more of SAS Spark and Google Cloud Platform (GCP).Hands-on experience with cloud analytics platforms (e.g. GCP Azure AWS) and big data technologies (e.g. Hadoop Spark).
• Strong technical skills in data mining and transformation with the ability to work confidently across structured and unstructured data and varied data with Agile methodologies and collaborative delivery in cross-functional teams.
• Experience with data visualisation tools such as Qlik Sense is a strong technical aptitude intellectual curiosity strong communication and interpersonal skills and a clear sense of ownership and accountability
• Strong communication skills with the ability to engage effectively with both operational teams and senior innovative initiatives and help shape the data science the use of data science to drive fact-based decision-making and behaviours across the function.
• Experience in a large corporate or institutional acquiring supporting the build or scaling of a new fraud operations function or product.
• Experience in financial crime fraud is beneficial but not essential. Knowledge of banking use cases and how they translate into data science solutions is a of scheme monitoring programmes (e.g. Visa Fraud Monitoring Program Mastercard Excessive Fraud Merchant thresholds).
• Sound knowledge of the Risk Management Framework (expert not required) preferably through previous role.

Youll achieve more at 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.

Personal data held by the Bank relating to employment applications will be used in accordance with our Privacy Statement which is available on our website.

***Issued By HSBC Electronic Data Processing (India) Private LTD***