Data Scientist (GenAI)

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.

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

WWe 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. In Technology, we're asking that you attend the office a minimum of 1 day per week.

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 data professionals 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:

Build, test and deploy machine learning models which will improve and/or automate decision making. 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. Implement comprehensive model monitoring. Develop model training and evaluation pipelines to accelerate model development / deployment adhering to software development best practices (CI/CD & MLOps) Engage with Engineering teams to ensure we capture data points that are relevant and useful for insights and modelling.

Requirements

You have at least 3-4 years of experience as a professional Data Scientist Python, which makes up the majority of our Data Science stack. Proven experience in data science, with a focus on machine learning model development/Large Language Model (LLM) application development. Experience deploying Generative AI applications to production in GCP (VertexAI) or AWS (Bedrock). Demonstrable experience monitoring the performance and output quality of generative models, including assessing/mitigating hallucinations and coherence of generated content. 

Desirables:

Experience fine-tuning large language models is a bonus. Prior experience utilising LLMs on mobile applications is a bonus. Experience with open-source large language models ( Llama).

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 - 60 mins technical interview with two team members Stage 4 - 45 min final with 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.