Data Scientist II - Financial Crime Solutions

13h13 hours ago

Mastercard

London, GB · Full-time · £65,000 – £85,000

About this role

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 are an award winning team with a proven track record of combining data science technique with intimate knowledge of payments data to aid Financial Institutions in their fight against money laundering and fraud.

You will directly contribute to project delivery by writing and reviewing code, delivering ML models, and managing a team. You will also perform proof-of-concept projects, engage in product design, and build prototypes using a full range of data science techniques.

You will work in close collaboration with engineering and operations data scientists, as well as the wider sales, consulting, and product teams. You will consider privacy, security, and regulation, along with the performance of your code and accuracy of your models.

You will have the opportunity to perform novel research to understand different criminal behaviours in payments data. You will think about how derived insights can be turned into new products and services, and write white papers, patents, and client facing data visualisations.

Requirements

Familiar with Python and standard data science libraries such as pandas, scikit-learn/xgboost, and networkx.
Keen to understand the data and model the behaviours it exposes.
Able to communicate with non-tech colleagues about technical matters and comfortable putting yourself in other people's shoes.
Happy and excited to explore new programming languages, technologies, and techniques.
Can-do attitude, pragmatic where necessary.
Interest in the financial services industry and want to tackle financial crime in the wider economy.
Excited by building products for clients and keen to engage in the design processes.

Responsibilities

Directly contribute to project delivery by writing code, reviewing code, and delivering ML models and analytics, as well as managing a team.
Perform proof-of-concept projects, engage in product design, and build prototypes.
Use the full range of data science techniques to develop new and novel algorithms for financial crime products.
Perform novel research to understand different criminal behaviours in payments data.
Think about how derived insights can be turned into new products and services for external clients.
Learn new technologies as required and engage with legacy and future technology stacks.
Write white papers, patents, and client facing data visualisations.
Consider privacy, security, and regulation, as well as the performance of your code and accuracy of your models.