Machine Learning Applied Scientist (Machine Learning Observability & Governance)

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

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. 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.

Responsibilties:

As a Machine Learning Applied Scientist in the Machine Learning Observability & Governance team, you will be instrumental in advancing Starling Bank's capabilities in safely and effectively exploiting AI and ML technologies. Your responsibilities will include:

Pioneering Novel Methods: Lead the development and implementation of innovative research-driven methods to deepen our understanding of AI and ML model behaviour in a production banking environment. Translating Research to Production: Bridge the gap between research and practical application by taking external knowledge (, from preprints, conferences) and transforming it into working code and frameworks for production systems, ensuring scalability and maintainability. Knowledge Dissemination: present research findings both internally and externally (, at conferences or through publications), to share advancements and foster a culture of continuous learning within the data practice. Collaborative Innovation: Work closely with data scientists, ML engineers, and other stakeholders to identify key challenges in ML observability and governance, and propose research-backed solutions.

Requirements

To succeed in this role, you should possess a strong academic foundation and practical experience in advanced machine learning and AI. We are looking for candidates with:

Research Experience: Demonstrated experience in a research-focused role, either in academia or industry, with a track record of contributing to or leading research projects. Industry Production Experience: Proven experience managing and deploying advanced ML/AI models in a production environment, understanding the complexities of real-world systems. Technical Proficiency: Strong programming skills in languages commonly used in ML and (, Python), and familiarity with relevant libraries and frameworks.

Desirable:

While not essential, the following experience would be highly beneficial:

Conference Presentation Experience: Experience presenting research findings at academic or industry conferences. Financial Services Context: An understanding of the financial services industry, including its unique challenges, regulatory landscape, and the application of AI within this sector. LLM Observability & Evaluation: Specific experience with the monitoring, evaluation, and governance of Large Language Models (LLMs) in production.

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 an 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.