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Starling Bank

Analytics Engineering - Team Lead (Fraud & AML)

Starling Bank is hiring an Analytics Engineering - Team Lead (Fraud & AML) in London, Cardiff and Manchester, United Kingdom. Level rates it ; you can apply on Starling Bank.

Level's read on this job

  • On Level's scale, this role is Little AI ●○○○: aI is not part of the work.
  • The posting allows some remote work.
  • Tools and skills the posting cites include analytics engineering, sql and data modeling.
  • Level classifies it as a lead role.
  • Level lists 41 other open roles at Starling Bank.

AI in this role

Lead the analytics engineering team focusing on fraud and anti-money laundering at a digital bank.

analytics-engineeringsqldata-modelingamlfraud-detection

Starling is the UK’s first and leading digital bank on a mission to fix banking! We built a new kind of bank because we knew technology had the power to help people save, spend and manage their money in a new and transformative way.

We’re a fully licensed UK bank with the culture and spirit of a fast-moving, disruptive tech company. We’re a bank, but better: fairer, easier to use and designed to demystify money for everyone. 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 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.

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. Hear from the team in our latest blogs or our case studies with Women in Tech.

We are looking for talented engineers 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.

Responsibilities

  • Manage and develop a team of analytics engineers.
  • Work closely with stakeholders to understand and prioritise key business needs.
  • Own and improve a large analytics estate serving many different business functions. 
  • Lead and deliver multiple workstreams end-to-end. 
  • Ensure quarterly priorities are delivered alongside standing work and ad hoc requests. 
  • Maintain Fraud & AML-related regular reporting. 
  • Support data science and ML model development and monitoring

Requirements

  • Extensive analytics engineering background with expert SQL and data modelling skills.
  • Hands-on experience with dbt (or similar framework) to build well-structured, tested, and maintainable data models.
  • Proficiency with Looker or a comparable BI tool.
  • Track record of managing, supporting, and developing analytics engineers.
  • Strong project management capabilities, including prioritising incoming work and delivering cross-functional data initiatives.
  • Excellent communication and documentation abilities.
  • Solid understanding of data governance and risk management.

Desirable Requirements

  • Experience working with fraud, AML or financial crime data
  • Experience in a regulated financial services environment
  • Experience with cloud data warehouses and CI/CD 
  • Experience with Git and peer-review workflows.

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 - 45 mins with one of the team
  • Stage 2 - Take-home challenge
  • Stage 3 - 60 mins technical interview with two team members
  • Stage 4 - 45 min final with an two executives

Benefits

  • 33 days holiday (including public holidays, which you can take when it 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
  • Incentives refer a friend scheme
  • 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. Individuals seeking employment at Starling Bank are considered without regard to race, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, physical or mental disability, military or veteran status, or any other characteristic protected by applicable law. 

When you provide us with this information, you are doing so at your own consent, with full knowledge that we will process this personal data in accordance with our Privacy Notice. By submitting your application, you agree that Starling Bank will collect your personal data for recruiting and related purposes. Our Privacy Notice explains what personal information we will process, where we will process your personal information, its purposes for processing your personal information, and the rights you can exercise over our use of your personal information.

How we rate this

Analytics Engineering - Team Lead (Fraud & AML) at Starling Bank rates 10 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Analytics EngineeringSQLData ModelingAmlFraud Detection

Questions you could be asked

  1. Tell me about a project where analytics engineering was part of your work. What did you do?
  2. Tell me about a project where sql was part of your work. What did you do?
  3. Tell me about a project where data modeling was part of your work. What did you do?
  4. Tell me about a project where aml was part of your work. What did you do?
  5. Tell me about a project where fraud detection was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Analytics Engineering, SQL, Data Modeling, Aml, and Fraud Detection. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.

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