Data Scientist (Computer Vision)

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 what your primary responsibilities may be. Innovation and collaboration will be at the core of everything you do. 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 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 our customers. This role sits within the Customer Identity & Financial Crime data division. This team is responsible for the deployment of analytical solutions and machine learning models to prevent and detect financial crime and better understand our customers. This role specifically will focus on the customer identity domain, with a focus on identity verification, KYC, and OCR technologies. Responsibilities: Build, test and deploy machine learning models which will improve and/or automate decision making. Collaborate with engineering, cyber, risk, and operational teams to identify appropriate data points that are relevant for modelling, using this insight to inform the creation of predictive models. Conduct exploratory data analysis to identify trends, patterns, and anomalies in customer identity data. Continuously monitor the performance of identity models in production and refine them to improve accuracy, scalability, and efficiency. Minimum Requirements: Demonstrable industry experience in Data Science/Machine Learning in Computer vision-related projects: Identity verification / KYC Computer vision OCR Anomaly detection Excellent skills in Python and SQL. Experience with libraries such as Scikit-learn, Tensorflow, Pytorch. Strong data wrangling skills for merging, cleaning, and sampling data. Strong data visualisation and communication skills. 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 with AWS/GCP. Desire to build explainable ML models (using techniques such as SHAP). Familiarity with data privacy regulations and experience in applying these to model development. 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. 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 two executives. 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. Starling Bank is an equal opportunity employer, and we’re proud of our ongoing efforts to foster diversity & inclusion in the workplace.

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