Data Scientist, Starling Bank
Fraud
Mobile-first bank offering personal, joint and business accounts
Be an early applicant
Mobile-first bank offering personal, joint and business accounts
1001+ employees
Be an early applicant
1001+ employees
Company mission
To solve our customer's problems - and build the best bank in the world.
Role
Who you are
- Industry experience in data science or machine learning models, ideally in fraud, financial crime, or a related domain
- Experience working with large-scale, high-dimensional, and heavily imbalanced datasets
- Excellent skills in Python and SQL
- Solid understanding of classification algorithms such as gradient boosting decision trees, including pros and cons of different model architectures
- Strong feature engineering skills and experience in transforming raw data into useful model inputs
- Effective communication skills and able to explain complex findings clearly to both technical and non-technical stakeholders
- Demonstrable experience deploying machine learning solutions in a production environment, and familiarity with version controls systems (e.g. Git)
Desirable
- Experience with cloud-based ML infrastructure, particularly GCP (Vertex AI, BigQuery), or equivalent (e.g. AWS, Azure)
- Exposure to orchestration tools such as Kubeflow pipelines or Airflow
- Familiarity with DBT or similar tools for modelling data in data warehouses
- Desire to build interpretable and explainable ML models (using techniques such as SHAP)
- Desire to quantify the level of fairness and bias machine learning models
- Enthusiasm for improving fraud detection systems and a proactive, problem-solving mindset
What the job involves
- 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 fraud patterns
Application process
- 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 3 - 45 min final with an executive and a member of the people team
Our take
Starling started life focused on consumer banking, it has since found most of its success by competing in the business banking space. Its caught up with Tide and beaten the likes of Monzo and Revolut to a more complete offering for businesses.
This progress resulted in the company receiving a £100M grant in April 2019 from a body created to boost competition in SME banking, which it has used to accelerate building a full suite of digital banking products: intelligent forecasting tools, and digitally-enabled relationship management functions, as well as lending products. Since then, it has gone on to raise significant rounds of funding with leading investors such as Goldman Sachs.
As well as continuing to expand in the UK, its expanding in Europe. And its imminently launching an international bank in Dublin, which has allowed it to offer its current account across the European Union post-Brexit
Banking for small businesses has historically been ignored, even though the experience is poor. Starling is in tune with knowing what its customers want, and continues to build out its range of third-party products within its banking app thanks to support from its open API. Having achieved profitability, it currently has 26 integrations, including Xero, but that figure continues to grow.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 11 rounds)
Apr 2022
$175.8m
LATE VC
Jun 2021
$47.2m
LATE VC
Total funding: $1.2bn
Company benefits
- Time off: 25 days holiday, plus your birthday as an extra freebie. You can also opt out of bank holidays and take them when works for you!
- Health insurance: Private health insurance with Vitality Health, one of the UK's leading private medical insurers
- Pension scheme
- Paid volunteering leave: We encourage all our employees to give back. You can take up to 16 hours paid leave a year, specifically to help causes meaningful to you
- Gym & cycle to work schemes: We offer discounted gym memberships and cycle to work schemes through salary sacrifice
- Perkbox: For a wide range of retail, entertainment and leisure discounts (as well as cash back) at a huge variety of businesses
Articles
Leadership
Anne Boden
(Founder)Held senior roles in finance over a 30 year career, including COO for AIB and Head of EMEA for RBS. Was CEO of the company for 9.5 years.
Raman Bhatia
(Group CEO)Previously CEO of OVO, Board Member at Bud, Head of Digital Bank (UK) at HSBC and VP at HouseTrip, among other roles.
Diversity, Equity & Inclusion at Starling Bank
Manuela Torrijos-Simon (Group Financial Controller)
- In the spirit of Aiming for Greatness and Doing the Right Thing, we want to be the bank with the best approach to Diversity and Inclusion
- The Always Open Forum at Starling empowers employees to come together and own their areas of interest, supporting their agenda both internally and externally
- The forum creates a safe space for conversations about all Diversity and Inclusion topics, with the spotlight currently on 3 focus areas; Race and Ethnicity, LGBTQ+ and Mental Health.
- We’re about to launch a new group to support Disability, and all of these teams help bring Starlings together to improve our workplace
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