Data Scientist (FinCrime and Customer Identity)

Starling Bank Limited
1 month ago
Create job alert

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’re a fully licensed UK bank with the culture and spirit of a fast-moving, disruptive tech company. We employ more than 3,000 people across our London, Southampton, Cardiff, and Manchester offices.

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 your primary responsibilities. Innovation and collaboration will be at the core of everything you do.

The way to thrive and shine within Starling is to be a self-driven individual and take full ownership of everything around you: from building things, designing, discovering, to sharing knowledge with your colleagues and ensuring 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 can interact and collaborate in person.

Our Data Environment

Our Data teams are aligned to divisions covering the following Banking Services & Products, Customer Identity & Financial Crime, and Data & ML Engineering. Our Data teams are excited about delivering meaningful and impactful insights to both the business and, more importantly, our customers.

We are looking for talented data professionals at all levels to join the team. We value people being engaged and caring about customers, 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 can do great things here at Starling, to continue changing banking for good.

Responsibilities:

  • You will be part of a team delivering data-driven solutions and insights to improve the speed, efficiency, and quality of decision-making.
  • Work proactively with technical and non-technical teams to deliver insights to support the wider business.
  • Build, test, and deploy machine learning models which will improve and/or automate decision making.
  • Provide insightful analytics across the bank to assist with decision making.
  • Engage with Engineering teams to ensure we capture data points that are relevant and useful for insights and modelling.

Minimum Requirements:

  • Demonstrable industry experiencein Data Science/Machine Learning inone or moreof:
    • Financial Crime
    • Anti-money laundering
    • Transaction monitoring
    • Anomaly detection
  • Excellent skills inPythonandSQL.
  • Experience with libraries such asScikit-learn, Tensorflow, Pytorch.
  • Strong data wrangling skills for merging, cleaning, and sampling data.
  • Strong data visualisation and communication skills are essential.
  • Understanding of the software development life cycle and experience using version control tools such as git.
  • Demonstrable experience deploying machine learning solutions in a production environment.

Desirables:

  • Experience withAWS/GCP.
  • Desire to build explainable ML models (using techniques such asSHAP).

Interview process

Interviewing is a two-way process and we want you to have the time and opportunity to get to know us, as much as we are getting to know you! Our interviews are conversational and we want to get the best from you, so come with questions and be curious. In general, you can expect the below, following a chat with one of our Talent Team:

  • Stage 1 - 30 mins with one of the team.
  • Stage 2 - Take home challenge.
  • Stage 3 - 90 mins technical interview with two team members.
  • Stage 4 - 45 min final with an executive and a member of the people team.

Benefits:

  • 25 days holiday (plus take your public holiday allowance whenever works best for you).
  • An extra day’s holiday for your birthday.
  • Annual leave is increased with length of service, and you can choose to buy or sell up to five extra days off.
  • 16 hours paid volunteering time a year.
  • Salary sacrifice, company enhanced pension scheme.
  • Life insurance at 4x your salary & group income protection.
  • Private Medical Insurance with VitalityHealth including mental health support and cancer care. Partner benefits include discounts with Waitrose, Mr & Mrs Smith, and Peloton.
  • Generous family-friendly policies.
  • Perkbox membership giving access to retail discounts, a wellness platform for physical and mental health, and weekly free and boosted perks.
  • Access to initiatives like Cycle to Work, Salary Sacrificed Gym partnerships, and Electric Vehicle (EV) leasing.

About Us

You may be put off applying for a role because you don't tick every box. Forget that! While we can’t accommodate every flexible working request, we're always open to discussion. So, if you're excited about working with us but aren’t sure if you're 100% there yet, get in touch anyway. We’re on a mission to radically reshape banking – and that starts with our brilliant team. Whatever came before, we’re proud to bring together people of all backgrounds and experiences who love working together to solve problems.

Starling Bank is an equal opportunity employer, and we’re proud of our ongoing efforts to foster diversity & inclusion in the workplace.

#J-18808-Ljbffr

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist- Consumer Behaviour

Lead Data Scientist

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.

Data Science Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Data science has become a linchpin in modern business, transforming oceans of raw data into actionable insights that guide strategy, product development, and personalised customer experiences. With this surge in data-centric operations, the need for effective data science leadership has never been more critical. Guiding a team of data scientists, analysts, and machine learning engineers requires not only technical acumen but also the ability to foster collaboration, champion ethical practices, and align complex modelling efforts with overarching business goals. This article provides practical guidance for managers and aspiring leaders aiming to excel in data-driven environments. By exploring strategies to motivate data science professionals, develop mentoring frameworks, and set achievable milestones, you will be better prepared to steer your team towards meaningful, evidence-based outcomes.

10 Essential Books to Read to Nail Your Data Science Career in the UK

Data science continues to be one of the most exciting and rapidly evolving fields in tech. With industries across the UK—ranging from finance and healthcare to e-commerce and government—embracing data-driven decision-making, the demand for skilled data scientists has soared. Whether you're a recent graduate looking for your first role or a professional aiming to advance your career, staying updated through books is crucial. In this article, we explore ten essential books every data science job seeker in the UK should read. Each book provides valuable insights into core concepts, practical applications, and industry-standard tools, helping you build skills employers are actively looking for.