Data Scientist (AML) (IT)

Data Scientist (AML) (IT)

Full-Time 36000 - 60000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Join our team to build and deploy machine learning models for fraud detection.
  • Company: Starling is the UK's leading digital bank, revolutionising banking with tech-driven solutions.
  • Benefits: Enjoy hybrid working, autonomy in projects, and a supportive team culture.
  • Why this job: Be part of a mission to change banking for good while working in an innovative environment.
  • Qualifications: We're looking for data enthusiasts with a passion for problem-solving and collaboration.
  • Other info: Minimum office attendance of 1 day per week; engage with a diverse team.

The predicted salary is between 36000 - 60000 £ per year.

Description

Starling is the UK's first and leading digital bank on a mission to fix banking! Our vision is fast technology, fair service, and honest values. All at the tap of a phone, all the time.

We are about giving customers a new way to spend, save and manage their money while taking better care of the planet which has seen us become a multi-award winning bank that now employs over 2800 across five offices in London, Cardiff, Dublin, Southampton, and Manchester. Our journey started in 2014, and since then we have surpassed 3.5 million accounts (and four account types!) with 350,000 business customers. We are a fully licensed UK bank but at the heart, we are a tech first company, enabling our platform to deliver brilliant products.

Our technologists are at the very heart of Starling and enjoy working in a fast-paced environment that is all about building things, creating new stuff, and disruptive technology that keeps us on the cutting edge of fintech. We operate a flat structure to empower you to make decisions regardless of what your primary responsibilities may be, innovation and collaboration will be at the core of everything you do. Help is never far away in our open culture, you will find support in your team and from across the business, we are in this together!

The way to thrive and shine within Starling is to be a self-driven individual and be able to take full ownership of everything around you: From building things, designing, discovering, to sharing knowledge with your colleagues and making sure all processes are efficient and productive to deliver the best possible results for our customers. Our purpose is underpinned by five Starling values: Listen, Keep It Simple, Do The Right Thing, Own It, and Aim For Greatness.

Hybrid Working

We have a Hybrid approach to working here at Starling – our preference is that you're located within a commutable distance of one of our offices so that we're able to interact and collaborate in person. In Technology, we're asking that you attend the office a minimum of 1 day per week.

Our Data Environment

Our Data teams are excited about the value of data within the business, powers our product decisions to improve things for our customers and enhance effective and agile decision making, regardless of what their primary tech stack may be. Hear from the team in our latest blogs or our case studies with Women in Tech .

We are looking for talented data professionals at all levels to join the team. We value people being engaged and caring about customers, caring about the code they write and the contribution they make to Starling. People with a broad ability to apply themselves to a multitude of problems and challenges, who can work across teams do great things here at Starling, to continue changing banking for good.

Ways of Working: We value autonomy – you'll be trusted to manage your own projects, drive modelling initiatives, and take ideas from concept to production
You'll be encouraged to propose new approaches and explore creative ways to detect and prevent fraud
We debate and critique our ideas in a healthy, supportive team
You'll have the chance to shape both models and how we think about fraud detection as a wider team

Responsibilities: You will be part of a team that builds, evaluates and deploys machine learning models to improve and automate decision making
Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions
Design and maintain robust feature engineering pipelines for modelling, working closely with analytics engineering teams
Contribute to the development of end-to-end machine learning workflows and help embed models into production systems
Analyse transaction and behavioural data to identify trends, anomalies, and AML patterns

Data Scientist (AML) (IT) employer: Starling Bank

Starling Bank is an exceptional employer that champions innovation and collaboration in a fast-paced, tech-driven environment. With a commitment to employee growth and a supportive culture, team members are empowered to take ownership of their projects while contributing to meaningful advancements in the banking sector. Located across multiple UK offices, Starling offers a hybrid working model that fosters both flexibility and teamwork, making it an ideal place for data professionals looking to make a significant impact.
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Contact Detail:

Starling Bank Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Data Scientist (AML) (IT)

✨Tip Number 1

Familiarise yourself with Starling's values: Listen, Keep It Simple, Do The Right Thing, Own It, and Aim For Greatness. Tailor your conversations and interactions to reflect these values, as they are central to the company culture.

✨Tip Number 2

Showcase your passion for data and technology by discussing recent projects or innovations you've been involved in. Highlight how you’ve used data to solve real-world problems, especially in fraud detection or AML.

✨Tip Number 3

Engage with the Data team’s blogs and case studies, particularly those related to Women in Tech. This will not only give you insights into their work but also provide talking points during interviews.

✨Tip Number 4

Prepare to discuss your experience with machine learning models and feature engineering pipelines. Be ready to explain how you can contribute to building effective fraud prevention tools and solutions.

We think you need these skills to ace Data Scientist (AML) (IT)

Machine Learning
Data Analysis
Feature Engineering
Fraud Detection Techniques
Statistical Modelling
Python or R Programming
SQL Proficiency
Collaboration Skills
Problem-Solving Skills
Data Visualisation
Understanding of AML Regulations
Agile Methodologies
Communication Skills
Critical Thinking

Some tips for your application 🫡

Understand the Company Culture: Familiarise yourself with Starling's mission and values. Highlight how your personal values align with theirs, especially around innovation, collaboration, and customer care.

Tailor Your CV: Make sure your CV reflects relevant experience in data science and machine learning, particularly in areas related to fraud detection and AML. Use specific examples that demonstrate your skills and achievements.

Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for fintech and your understanding of the role. Discuss how you can contribute to Starling's goals and mention any innovative ideas you have for improving their fraud detection processes.

Showcase Your Technical Skills: In your application, emphasise your technical expertise in machine learning, data analysis, and feature engineering. Provide examples of projects where you've successfully applied these skills, particularly in a collaborative environment.

How to prepare for a job interview at Starling Bank

✨Understand the Company Values

Familiarise yourself with Starling's core values: Listen, Keep It Simple, Do The Right Thing, Own It, and Aim For Greatness. Be prepared to discuss how these values resonate with your own work ethic and experiences.

✨Showcase Your Technical Skills

As a Data Scientist, you'll need to demonstrate your proficiency in machine learning and data analysis. Prepare examples of past projects where you've built or deployed models, and be ready to discuss the tools and techniques you used.

✨Prepare for Collaborative Scenarios

Starling values collaboration across teams. Think of instances where you've worked with both technical and non-technical colleagues to solve problems. Be ready to share how you communicated complex ideas effectively.

✨Emphasise Your Problem-Solving Approach

The role involves tackling challenges related to fraud detection and prevention. Be prepared to discuss your approach to problem-solving, including how you analyse data to identify trends and anomalies.

Data Scientist (AML) (IT)
Starling Bank
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  • Data Scientist (AML) (IT)

    Full-Time
    36000 - 60000 £ / year (est.)

    Application deadline: 2027-07-18

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    Starling Bank

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