Data Scientist - Customer - Manchester

Starling Bank
Manchester
2 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist/Machine Learning Engineer - RNA Design

Data Scientist - active NPPV3 required

Data Scientist - London

Data Scientist | London | AI-Powered SaaS Company

Starling is the UK’s first and leading digital bank ona mission to fix banking! Our vision is fast technology, fairservice, and honest values. All at the tap of a phone, all thetime.Starling is the UK’s first and leading digital bank on amission to fix banking! We built a new kind of bank because we knewtechnology had the power to help people save, spend and managetheir money in a new and transformative way.We’re a fully licensedUK bank with the culture and spirit of a fast-moving, disruptivetech company. We’re a bank, but better: fairer, easier to use anddesigned to demystify money for everyone. We employ more than 3,000people across our London, Southampton, Cardiff and Manchesteroffices.Our technologists are at the very heart of Starling andenjoy working in a fast-paced environment that is all aboutbuilding things, creating new stuff, and disruptive technology thatkeeps us on the cutting edge of fintech. We operate a flatstructure to empower you to make decisions regardless of what yourprimary responsibilities may be, innovation and collaboration willbe at the core of everything you do. Help is never far away in ouropen culture, you will find support in your team and from acrossthe business, we are in this together!The way to thrive and shinewithin Starling is to be a self-driven individual and be able totake full ownership of everything around you: From building things,designing, discovering, to sharing knowledge with your colleaguesand making sure all processes are efficient and productive todeliver the best possible results for our customers. Our purpose isunderpinned by five Starling values: Listen, Keep It Simple, Do TheRight Thing, Own It, and Aim For Greatness.Hybrid WorkingWe have aHybrid approach to working here at Starling - our preference isthat you/'re located within a commutable distance of one of ouroffices so that we/'re able to interact and collaborate inperson.Our Data EnvironmentOur Data teams are aligned to divisionscovering the following Banking Services & Products, CustomerIdentity & Financial Crime and Data & ML Engineering. OurData teams are excited about delivering meaningful and impactfulinsights to both the business and more importantly our customers.Hear from the team in our latest blogs or our case studies withWomen in Tech.We are looking for talented data professionals at alllevels to join the team. We value people being engaged and caringabout customers, caring about the code they write and thecontribution they make to Starling. People with a broad ability toapply themselves to a multitude of problems and challenges, who canwork across teams do great things here at Starling, to continuechanging banking for good.Responsibilities: Translate datarequirements from across the organisation into robust and reusablemodels Considerations towards model risk and governance Maintainconsistent and clear documentation and communicate with businessstakeholders (both technical and non-technical) Collaborate withthe wider data team to help meet the business goals, including peerreviews  Self-starter with ability to think outside the boxand evolve projects. Take ownership of a project end-to-end andmanage priorities accordingly Requirements Experience with ConsumerBehaviour Modelling. To include but not limited to: VulnerableCustomer Identification Transaction models i.e. Gambling, Spending,Income Deriving insights from banking data and third party externaldata Model Monitoring Strong experience with SQL & Python Experience supporting and working with cross-functional teams in adynamic environment Model deployment Version control using GitHubor similar Desirables: Strong experience with dbt, dimensionalmodelling, GCP and Looker or a desire to learn Third party dataacquisition Interview processInterviewing is a two way process andwe want you to have the time and opportunity to get to know us, asmuch as we are getting to know you! Our interviews areconversational and we want to get the best from you, so come withquestions and be curious. In general you can expect the below,following a chat with one of our Talent Team: Stage 1 - 30 minswith one of the team Stage 2 - Take-home challenge Stage 3 - 60mins technical interview with two team members Stage 4 - 45 minfinal with an two executives Benefits 33 days holiday (includingpublic holidays, which you can take when it works best for you) Anextra day’s holiday for your birthday Annual leave is increasedwith length of service, and you can choose to buy or sell up tofive extra days off 16 hours paid volunteering time a year Salarysacrifice, company enhanced pension scheme Life insurance at 4xyour salary & group income protection Private Medical Insurancewith VitalityHealth including mental health support and cancercare. Partner benefits include discounts with Waitrose, Mr&MrsSmith and Peloton Generous family-friendly policies Incentivesrefer a friend scheme Perkbox membership giving access to retaildiscounts, a wellness platform for physical and mental health, andweekly free and boosted perks Access to initiatives like Cycle toWork, Salary Sacrificed Gym partnerships and Electric Vehicle (EV)leasing About usYou may be put off applying for a role because youdon/'t tick every box. Forget that! While we can’t accommodateevery flexible working request, we/'re always open to discussion.So, if you/'re excited about working with us, but aren’t sure ifyou/'re 100% there yet, get in touch anyway. We’re on a mission toradically reshape banking – and that starts with our brilliantteam. Whatever came before, we’re proud to bring together people ofall backgrounds and experiences who love working together to solveproblems.Starling Bank is an equal opportunity employer, and we’reproud of our ongoing efforts to foster diversity & inclusion inthe workplace. Individuals seeking employment at Starling Bank areconsidered without regard to race, religion, national origin, age,sex, gender, gender identity, gender expression, sexualorientation, marital status, medical condition, ancestry, physicalor mental disability, military or veteran status, or any othercharacteristic protected by applicable law. When you provide uswith this information, you are doing so at your own consent, withfull knowledge that we will process this personal data inaccordance with our Privacy Notice.By submitting your application,you agree that Starling Bank may collect your personal data forrecruiting and related purposes. Our Privacy Notice explains whatpersonal information we may process, where we may process yourpersonal information, its purposes for processing your personalinformation, and the rights you can exercise over our use of yourpersonal 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.