AP Data Scientist - Financial Crime

Mastercard
SingaporePosted 30 March 2026

Job Description

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 Data Scientist - Financial Crime Director, 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 Director of Data Science, you will be the senior technical and public representative of the Data Science Centre of Excellence in Asia‑Pacific. You will act as a visible thought leader for Mastercard’s financial crime capabilities, representing the organisation at conferences, industry forums, and senior customer engagements, and contributing to the wider industry discourse through white papers and technical publications. Alongside this external mandate, you will remain hands‑on and technically engaged, working closely with other data scientists and local teams to guide the design, development, and evolution of regional financial crime models. In partnership with Product and the global Data Science team you will ensure delivery is realistic and balanced between global standards and local adaptation. Ultimately, you will be accountable for both the effectiveness of regional delivery and the external credibility and reputation of the Centre of Excellence. In this position, you will: • Plan and prioritise regional data science work, staying hands‑on in key technical discussions to ensure delivery meets customer needs and operates within product, platform, and technology constraints. • Take a big‑picture view of regional demand, translating customer requirements, regulatory expectations, and solution limitations into realistic delivery plans. • Act as the senior regional authority on financial crime modelling, guiding model design, and governance, and engaging directly with customers across Asia Pacific as a trusted technical advisor. • Represent Mastercard and the Centre of Excellence externally through conferences, industry forums, and publishing white papers. • Collaborate with global Data Science and Product teams to align on methodology and model strategy, while owning regional contextualisation and execution. • Support proof‑of‑value initiatives and targeted deployments, ensuring insights and experimental work are tran ... (truncated, view full listing at source)
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