AP Lead Data Scientist – Financial Crime

Mastercard; Singapore; Sur place; SGD 180 000 - 240 000; Plein temps

Résumé du poste

Mastercard is seeking an AP Lead Data Scientist for Financial Crime to join a new Centre of Excellence in Asia-Pacific. You will build and maintain models to detect fraud, scams, and money laundering using payment data and collaborate with regional and global teams to align on methodology and strategy.

You will contribute to local data science capabilities, publish insights, and ensure compliance with privacy, security, and regulatory guidelines while delivering value to regional clients.

Qualifications

• Strong Python and data science library experience (pandas, polars, scikit-learn, networkx).
• Experience delivering data science solutions in regulated/payments contexts.
• Ability to communicate with non-technical colleagues about technical matters.

Responsabilités

• Build and maintain data science models to detect fraud, scams, and money laundering using payments data.
• Collaborate with regional and global data science and product teams to align on methodology and model strategy.
• Write white papers, patents, and client-facing data visualisations.
• Consider privacy, security, and regulatory requirements in all work.

Connaissances

Python

pandas

polars

scikit-learn

networkx

algorithm development

communication

new technologies

regulated/payments knowledge

English fluent

Formation

Advanced data science degree

Outils

Real-time data processing

Deep learning frameworks

Data visualization

Description du poste

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary

AP Lead Data Scientist – Financial Crime

Lead Data Scientist – Financial Crime

Who is Mastercard?

Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential.

Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.

Overview

In the Financial Crime Solutions (FCS) team at Mastercard, we build and deliver products and services powered by payment data to detect and prevent financial crime. We are an award winning team, combining advanced data science with deep payment expertise to help financial institutions combat fraud, scams, and money laundering by uncovering the criminal behaviours that drive them.

We are now building a new Centre of Excellence in Asia-Pacific, designed to act as a regional hub for the Cyber & FCS vertical. The Centre will drive scalable growth and robust delivery tailored to APAC priorities, and strengthen Mastercard’s leadership in anti scam and fraud prevention through thought leadership and industry engagement.

Role

As a Lead Data Scientist, you will be a core contributor to a newly established Centre of Excellence, building and maintaining data science models that help detect fraud, scams, and money laundering using payments data.

In the research discipline you will help build systems that expose money laundering and detect fraud as well as work with the other data scientists and clients to understand the underlying behaviours employed by criminals. You will be product focused, working in close collaboration with the regional team.

A key aspect of this role is building and sustaining local data science capabilities within the Centre of Excellence, ensuring we can effectively support customers across Asia Pacific while remaining closely aligned with global strategy and guidance. This includes acting as regional experts in the development, maintenance, and application of financial crime models, enabling timely, context aware support for our regional clients.

In this position, you will

• Perform proof-of-concept projects, engage in product design and build prototypes.
• Use the full range of data science based techniques to develop new and novel algorithms to aid existing and new financial crime products.
• Be able to perform novel research to help us and our clients 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.
• Be ready to 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. This means considering privacy, security, and regulation, as well as the performance of your code and the accuracy of your models.
• Act as a regional expert in building, maintaining, and evolving financial crime models, ensuring they remain effective, well understood, and appropriately governed.
• Support customers across Asia Pacific by providing data science guidance and services, informed by global frameworks while tailored to local market needs and constraints.
• 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, while owning regional execution and contextualisation.
• Enable scalable customer support by strengthening local DS ownership, reducing dependency on global teams for region specific model understanding and application.

Skills Required

Your passion is focused on the design of algorithms to solve real, pressing problems using data. You will have an interest in the financial services industry and want to tackle financial crime in the wider economy. You are excited by building products for clients and are keen to engage in the design processes this involves. Specifically:

• You can write Python to a high standard and are familiar with the standard data science libraries such as pandas, polars, scikit-learn and networkx.
• You are capable of developing new algorithms in novel situations and can demonstrate previous work to evidence this.
• You are keen to understand the data we work with and have a keen interest in how to model the behaviours it exposes.
• You are able to communicate with non-tech colleagues about technical matters, and you are comfortable putting yourself in other people's shoes.
• You are happy and excited to explore new technologies and techniques.
• You have a can-do attitude, can be pragmatic where necessary, and are excited to work as part of a specialist team. You can engage in constructive criticism and aren't afraid to have your code reviewed.
• You had professional exposure delivering data science solutions, ideally within a regulated or payments adjacent environment and with an understanding of regional market, customer, and regulatory considerations.
• Comfortable operating in a federated model, balancing global standards and guidance with local ownership, execution, and customer engagement.
• Fluent in English

As we are often breaking new ground, both for Mastercard and more widely in our sector, we strongly encourage exploring new technologies and techniques. Some of the following experience is therefore desirable:

• A strong academic foundation in a scientific or closely related discipline, such as data science, computer science, mathematics, statistics, physics, or engineering
• Streaming and real time data processing
• Modern machine learning approaches, including deep learning frameworks
• Network and graph based analysis to model complex behaviours.
• Development of custom data visualisations and analytical prototypes

Corporate Security Responsibility

• Abide by Mastercard’s security policies and practices;
• Ensure the confidentiality and integrity of the information being accessed;
• Report any suspected information security violation or breach, and
• Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.