Data Scientist (GenAI - Customer Identity) - Manchester

Starling Bank
Manchester
3 days ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist - Production

Data Scientist/Machine Learning Engineer - RNA Design

Data Scientist - active NPPV3 required

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 WorkingWe 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 EnvironmentOur 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 (e.g Llama). Interview processInterviewing 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 usYou 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 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.

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.