Description
Mastercard is building a new Centre of Excellence in Asia-Pacific, designed to act as a regional hub for the Cyber & Financial Crime Solutions (FCS) vertical. As a Lead Data Scientist, you will be a core contributor to this centre, building and maintaining data science models that help detect fraud, scams, and money laundering using payments data.
In this role, you will:
- Perform proof-of-concept projects, engage in product design, and build prototypes.
- Develop new and novel algorithms to aid existing and new financial crime products using data science techniques.
- Conduct research to help understand the different criminal behaviours in payments data.
- Think about how derived insights can be turned into new products and services we can offer to external clients.
- Learn new technologies as required and engage with various technology stacks.
- Write white papers, patents, and client-facing data visualisations.
- Consider the full impact of your work, including privacy, security, and regulation.
- Act as a regional expert in building, maintaining, and evolving financial crime models.
- Support customers across Asia Pacific by providing data science guidance and services.
- Contribute to and support regional initiatives such as proof of value exercises and targeted solution deployments.
- Collaborate closely with global data science and product teams to align on methodology, research direction, and model strategy.
The successful candidate will have:
- A passion for designing algorithms to solve real, pressing problems using data.
- An interest in the financial services industry and a desire to tackle financial crime.
- Experience writing Python to a high standard and familiarity with standard data science libraries.
- The ability to develop new algorithms in novel situations and demonstrate previous work.
- A keen interest in understanding the data and modelling the behaviours it exposes.
- Excellent communication skills and the ability to put yourself in other people's shoes.
- A can-do attitude and a willingness to work as part of a specialist team.