Lead Data Scientist

Mastercard; Greater London; On-site; GBP 70,000 - 90,000; Full time

Job summary

A global technology company is seeking a Lead Data Scientist to join their Financial Crime Solutions team. In this role, you'll develop innovative algorithms to combat financial crime using payments data. You will work closely with engineering teams and engage in product design and proof-of-concept projects. Ideal candidates will possess strong Python skills and experience with data science libraries. This position is based in London and offers the opportunity to tackle real-world financial crime challenges.

Qualifications

• Strong Python skills with proficiency in standard data science libraries.
• Experience developing algorithms and evidence of previous work.
• Ability to model and understand data behaviors.

Responsibilities

• Perform proof-of-concept projects and engage in product design.
• Develop new algorithms to enhance financial crime products.
• Conduct research to understand criminal behaviors in payments data.
• Create white papers and client-facing data visualizations.

Skills

Python programming

Data science libraries (pandas, scikit-learn)

Algorithm design

Communication with non-technical colleagues

Exploration of new programming languages and technologies

Tools

Kafka

TensorFlow

TensorFlow

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

Lead Data Scientist

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 team at Mastercard, we build and deliver products and services powered by payments data to find and stop financial crime. We’re an award‑winning team with a proven track record of combining data science technique with an intimate knowledge of payments data to aid Financial Institutions in their fight against money laundering and fraud. Headquartered in The City of London, and operating globally, we craft bespoke algorithms that help our clients gain an understanding of the underlying criminal behaviour that drives financial crime, empowering them to take action.

Role

As a Data Scientist, you will join one of the first teams in the world looking at payments data in the UK and across the world. 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 our engineering and operations data scientists as well as the wider sales, consulting, and product teams.

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 legacy and future technology stacks, in the UK and internationally.
• 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.

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.

• You can write Python to a high standard and are familiar with the standard data science libraries such as pandas, 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 programming languages, 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.

Desirable additional experience

• Practical experience using streaming technologies, including streaming platforms (e.g. Kafka), online algorithms (e.g. stochastic gradient descent), and fixed‑memory data structures (e.g. Bloom Filters).
• Experience using next generation machine learning techniques and tools, including Deep Neural Networks and TensorFlow.
• Exposure to Network Theory, especially social network analysis and graph diffusion analysis. Ability to build custom data visualisations, prototype browser based UX/UI, and the server side microservices to support them.

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.