Senior Data Scientist

Mastercard; Greater London; On-site; GBP 95,000 - 130,000; Full time

Job summary

Mastercard is seeking a Senior Data Scientist to join the Financial Crime Solutions Data Science team. You will develop, deploy, and support machine learning solutions that prevent financial crime across the global payments ecosystem, with a focus on A2A fraud, scam, and mule detection.

The role requires strong Python skills, experience with large-scale datasets, and the ability to deliver measurable value to customers through data-driven solutions.

Qualifications

• Experience developing, evaluating, and deploying machine learning models in a commercial environment.
• Strong proficiency in Python for data science and machine learning.
• Experience working with structured and large-scale datasets.
• Ability to apply scientific thinking and sound analytical approaches to solve complex problems.

Responsibilities

• Configure, validate, and deploy machine learning models to customers around the world.
• Conduct Proof-of-Value exercises with customers to demonstrate model performance and business impact.
• Contribute to the research, development, and evaluation of new fraud, scam, and mule detection solutions.
• Support and improve production models as customer needs and fraud patterns evolve.
• Partner with Product, Customer Delivery, and Data Science colleagues to enhance our solutions and deliver greater customer value.
• Analyse complex datasets to identify opportunities for improved detection performance and customer outcomes.
• Contribute to a culture of learning, continuous improvement, and practical problem solving.

Skills

Python

Data analysis

Model deployment

Communication

Cross-functional collaboration

Tools

PySpark

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

Senior Data Scientist

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.

The Financial Crime Solutions Data Science team is looking for a Senior Data Scientist to join the team and help develop, deploy, and support machine learning solutions that prevent financial crime across the global payments ecosystem.

This role is primarily focused on Account-to-Account (A2A) fraud, scam, and mule detection, helping financial institutions identify and stop increasingly sophisticated forms of financial crime. The ideal candidate combines strong analytical skills with a practical mindset and is passionate about delivering solutions that create measurable value for customers.

Successful candidates are intellectually curious, evidence-driven, and motivated by solving challenging real-world problems. They thrive in environments where learning, adaptability, and ownership are valued and where data science is expected to deliver tangible outcomes.

Role

In This Position, You Will

• Configure, validate, and deploy machine learning models to customers around the world.
• Conduct Proof-of-Value exercises with customers to demonstrate model performance and business impact.
• Contribute to the research, development, and evaluation of new fraud, scam, and mule detection solutions.
• Support and improve production models as customer needs and fraud patterns evolve.
• Partner with Product, Customer Delivery, and Data Science colleagues to enhance our solutions and deliver greater customer value.
• Analyse complex datasets to identify opportunities for improved detection performance and customer outcomes.
• Contribute to a culture of learning, continuous improvement, and practical problem solving.

All About You

• Experience developing, evaluating, and deploying machine learning models in a commercial environment.
• Strong proficiency in Python for data science and machine learning.
• Experience working with structured and large-scale datasets.
• Ability to apply scientific thinking and sound analytical approaches to solve complex problems.
• Strong communication skills, with the ability to explain technical concepts and results to a variety of audiences.
• Curiosity and a willingness to challenge assumptions, learn new approaches, and continuously improve solutions.
• Ability to work independently while collaborating effectively across teams.
• A customer-focused mindset and an interest in understanding how data science creates real-world value.

Desirable

• Experience with PySpark and distributed data processing.
• Experience building machine learning solutions for fraud, scams, mule detection, or broader financial crime use cases.
• Knowledge of the Account-to-Account (A2A) payments ecosystem.
• Familiarity with modern software development and model deployment practices.
• Experience working with payment, banking, or financial services data.

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.