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
Requirements
Industry experience in data science or machine learning models, ideally in AML, 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 Effectivemunication skills and able to explainplex 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 ( Git)
Desirables:
Experience with cloud-based ML infrastructure, particularly GCP (Vertex AI, BigQuery), or equivalent ( 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
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, soe 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 3 - 45 min final with an executive and a member of the people team
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,pany enhanced pension scheme Life insurance at 4x your salary & group ie 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 amodate 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 may collect your personal data for recruiting and related purposes. Our Privacy Notice explains what personal information we may process, where we may process your personal information, its purposes for processing your personal information, and the rights you can exercise over our use of your personal information. Job ID 924589EC5D
