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Data Scientist - Cyber

The role

Apply Job ID R96685 Location: London
White Collar Factory (95009), United Kingdom, London, London

At Capital One, we’re building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit. We are succeeding because they are succeeding.                                               

Guided by our shared values, we thrive in an environment where collaboration and openness are valued. We believe that innovation is powered by perspective and that teamwork and respect for each other lead to superior results. We elevate each other and obsess about doing the right thing. Our associates serve with humility and a deep respect for their responsibility in helping our customers achieve their goals and realize their dreams. Together, we are on a quest to change banking for good.

Data Scientist - Cyber

Threat modelling is the practice of examining software and systems from the design phase forward to identify and eliminate insecure patterns before they manifest in production code. Threat modelling ensures that software and systems continue to evolve securely as new features are added. Capital One aims to fully embed threat modelling across the software delivery lifecycle, ensuring that all Capital One software is measurably secure by design. As part of that initiative, we aim to develop software tools to enable engineers to threat model.

As a data scientist working in the Enterprise Threat Modelling team, you will be delivering data-driven tools that empower engineers to threat model. These tools aim to capture and track all threat modelling activity across the enterprise, and deliver on our mission to provide meaningful measurements of the quality and value of threat models. The features you will be adding to our tooling ecosystem will aim to drive down the cost of threat modelling to engineering teams, while also driving up the quality and visibility of the threat models that are produced.

You will be working with a diverse team including Threat Modelling Engineers, Data Scientists and Front and Backend software engineers to deliver data-driven tools for discovering and identifying threats in architectures and software designs.

As a data scientist working on this project we’ll be looking for you to develop the data driven aspects of the tools. This will involve working on a diverse set of data-centric problems including: 

  • Establishing key metrics for threat model quality and associated visualisation for end user consumption that drive improvements in threat modelling practice across the enterprise

  • Using data collected from the user interface to understand key areas of friction for the user

  • Leveraging NLP technology to automate the discovery of architectural constructs and patterns in use for a project that is being threat modelled from issue trackers, code repositories and wiki pages

  • Building a threat recommendation engine that automates the suggestion of relevant threats to a team based on the similarity of an architecture to other known architectures

About you

  • You thrive in a collaborative and collegial team that employs Agile and Scrum practices to deliver at pace with high visibility

  • You are a self-starter who seeks opportunities to innovate and bring new ways of thinking to a team

  • You have a product mindset, and you seek customer and stakeholder feedback on your work and strive to use that feedback to improve the features you deliver

  • You value high quality and secure code with good documentation and full test coverage

  • You value and seek to understand the context of your work

  • You are naturally curious, and always looking to learn new technologies and stay at the leading edge of technology. You enjoy bringing new technologies and practices to the team

This role requires a range of skills, including:

  • Experience with Python and the data science ecosystem including Pandas, Numpy, scipy, scikit-learn, NLTK etc

  • Experience with linked data and semantic web technologies for building knowledge graphs

  • Experience with building recommendation engines

  • The ability to design visualisations and dashboards that provide meaningful and actionable insights for users

  • Expertise at working with structured and unstructured data from a variety of sources including APIs, object stores, and relational and non-relational databases

  • The ability to produce data pipelines using tools such as Airflow 

  • Capability to build APIs for exposing analytics to other consumers

  • A drive to work with front-end and back-end engineers to deliver analytic products from inception to production

  • Agile and Scrum working practices and ceremonies

Experience in some of the following is preferred:

  • Experience with leveraging Python frameworks for backend API services

  • Experience with using javascript for front-end visualisations and dashboards

  • Expertise with modern DevOps practices, including familiarity with CI/CD processes, and associated technologies such as Jenkins and Artifactory

  • Working in a Cloud environment, AWS preferred

  • Experience using containerisation technologies including Docker and Kubernetes

  • Developing Cyber security focused applications, tools and services

  • Developing and contributing to open source software, and a keen desire to make your work relevant and available to the open source community

Capital One is committed to diversity in the workplace.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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The benefits

Health

Live a healthy life with our private health insurance which is free for your family.

Fitness

Stay in shape with our on-site gym in Nottingham and rooftop running track in London.

Wellbeing

Work-life balance is important to us. So, we are open to flexible working to support your lifestyle.

Finances

We are able to support you with relocation if needed. And we offer an interest-free travel ticket and stock purchase plan.

Training

You'll get access to vast amounts of internal and external conferences and a dedicated internal training platform.

Community

We are proud to support our local tech communities with various meet-ups and events for you to get involved in.

Cyber at Capital One

The UK Cyber team is part of the bigger US Cyber enterprise. This means that the UK Cyber team benefits from small company agility with big company resources.

As one of the UK’s top ten credit card providers, keeping our millions of customers safe is vital to our business. For a Cyber professional like you, that means an opportunity to make a difference, learn and grow.

We’re making finance simpler and more human. So our cutting-edge products need to work for our consumers as well as being super secure.

In Cyber at Capital One, we do things at a fast pace in a CI/CD environment. We’re not a normal financial services company constrained by a fixed mindset and legacy systems.

We’re an AGILE business that dreams big and has the resources to deliver big (our largest systems are already 100% in the Cloud). We’re doing whatever it takes to protect our customers; the smartest new people, new technologies, new products, new ideas, new ways of thinking and working.

We invest in our Cyber team, using leading edge tech, our in-house Tech College and external training to keep the team ahead of the curve.

We play an active part in the wider community, hosting Cyber MeetUps at our offices in London, and sponsoring, promoting and attending Cyber events throughout the year.

Find out more about Capital One here.

"The Capital One UK Cyber business benefits from small company agility with big company resources."

Dicky Stafford, Director of Cyber Engineering

Life at Capital One

We’re a financial services company with a tech mindset that runs throughout the business, setting us apart from others in the industry.

Are you the right fit?

  • You see opportunities to innovate and disrupt where others see obstacles and hurdles. You tell others how they can do something rather than telling them why they can’t.

  • You can convince, explain and reassure people at all levels, from business managers to developers.

  • You have an appetite to learn and enjoy the challenge of doing things that haven’t been done before (data streaming, machine learning). You apply rigorous engineering sense to deliver robust business servicing applications.

  • You’re not afraid to challenge the status quo.

Success profile

  • A passion for learning and innovating 

    A lot of what we do is new, so you’ll learn by immersing yourself in the wider community, developing yourself and your team along the way.

  • High quality work 

    We work in a rapidly changing business, so you’ll need a focus on delivering high quality work at a fast pace. Doing the right thing quickly is good; quick and dirty just won’t cut it.

  • Team player 

    We have a ‘wade in and help’ mindset in Cyber. You’ll thrive on getting stuck in. You’ll give your own opinions, share your experiences and perspectives, and listen to those of colleagues. In doing so, you’ll learn and help others in the team learn from you.

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