Manager, Data Scientist

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Mastercard

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Mastercard

Manager, Data Scientist

London

In office

Description

The Payment Security & Risk Data Science team are looking for a Data Scientist to join the team and help develop, deploy and support our suite of models used to prevent financial crime globally. The ideal candidate has experience working in financial crimes, and is passionate about stopping it. They’re also intellectually curious, naturally analytical, and have a drive to create customer value in all the work they do.

Role

In this position, you will:

• Perform proof-of-concept projects, engage in product design and build prototypes.

• Collaborate across different business teams to gather requirements and develop projects to deliver on agreed outputs

• 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.

All About You

The ideal candidate for this position should:

Essential

• Have experience developing and deploying machine learning models at scale.

• Have experience of working in a scientific manner and creating high-quality results.

• Be able to effectively explain complex technical concepts and results to a wide variety of audiences – in both written and verbal settings.

• Be able to take a Product lens to work – thinking about the customers value as the primary goal of everything we do

Desirable

• Experience with the following: Unix CLI, Python, GoLang, Java, Dagster, MLFlow, Hadoop, Snowflake

• Experience building fraud / scam / money laundering models.

• Knowledge of the payments ecosystem

• Knowledge of blockchain / crypto ecosystem