Responsibilities
- 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
- Directly contribute to project delivery – writing code, reviewing code, and delivering ML models and analytics, as well as managing a team, with responsibility for engaging with Product and Engineering counterparts on a specific product or series of projects
- 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
Qualifications
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. Specifically: You are capable of developing new algorithms in novel situations and can demonstrate previous work to evidence this. 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, or design decisions discussed. 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 can write Python to a high standard and are familiar with the standard data science libraries such as pandas, scikit-learn/xgboost and networkx. You are happy and excited to explore new programming languages, technologies, and techniques. 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. Specific experience in Account to Account payments, Card Payments, or the Payments industry more broadly. Ability to build custom data visualisations, prototype browser based UX/UI, and the server side microservices to support them.
Benefits
- Gym membership
- Pension plan
- Share purchase options
- Extra holiday purchase optional
- 25 days holiday (excluding bank holidays)
- Work from home opportunities
- Health insurance
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