Data Scientist (FinCrime and Customer Identity) - DS-1 [HighSalary]
Data Scientist (FinCrime and Customer Identity) - DS-1 [HighSalary]

Data Scientist (FinCrime and Customer Identity) - DS-1 [HighSalary]

London Full-Time 43200 - 72000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Join our team to deliver data-driven solutions and insights that enhance decision-making.
  • Company: Starling is the UK's leading digital bank, revolutionizing banking with technology and fair service.
  • Benefits: Enjoy 25 days holiday, private medical insurance, and perks like discounts and wellness programs.
  • Why this job: Be part of a fast-paced, innovative culture where your ideas can truly make an impact.
  • Qualifications: Experience in Data Science/Machine Learning, especially in Financial Crime, is preferred but not mandatory.
  • Other info: We value attitude over experience; if you're passionate, we want to hear from you!

The predicted salary is between 43200 - 72000 £ per year.

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: 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 Build, test and deploy machine learning models which will improve and/or automate decision making Provide insightful analytics across the bank to assist with decision making Engage with Engineering teams to ensure we capture data points that are relevant and useful for insights and modelling RequirementsWe’re open-minded when it comes to hiring and we care more about aptitude and attitude than specific experience or qualifications. We think the ideal candidate will encompass most of the following: Demonstrable industry experience Data Science/Machine Learning in one or more of: Financial Crime Anti-money laundering Transaction monitoring 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 are essential 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) 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 – 90 mins technical interview with two team members Stage 3 – 45 min final with an executive and a member of the people team Benefits 25 days holiday (plus take your public holiday allowance whenever 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 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 will collect your personal data for recruiting and related purposes. Our Privacy Notice explains what personal information we will process, where we will process your personal information, its purposes for processing your personal information, and the rights you can exercise over our use of your personal information.

Data Scientist (FinCrime and Customer Identity) - DS-1 [HighSalary] employer: Starling Bank

At Starling, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our commitment to employee growth is evident through our comprehensive benefits package, including generous holiday allowances, private medical insurance, and opportunities for professional development. Located in the heart of the UK, our offices provide a vibrant environment where you can thrive as part of a diverse team dedicated to reshaping banking for the better.
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Contact Detail:

Starling Bank Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Data Scientist (FinCrime and Customer Identity) - DS-1 [HighSalary]

✨Tip Number 1

Familiarize yourself with Starling's values: Listen, Keep It Simple, Do The Right Thing, Own It, and Aim For Greatness. Demonstrating how you embody these values in your interactions can set you apart during the interview process.

✨Tip Number 2

Prepare to discuss your experience with machine learning models, especially in the context of financial crime and customer identity. Be ready to share specific examples of how you've built, tested, and deployed these models in a production environment.

✨Tip Number 3

Engage with the data community by reading blogs or case studies related to Starling's data teams. This will not only give you insights into their work but also provide you with relevant topics to discuss during your interviews.

✨Tip Number 4

Show your curiosity during the interview process. Prepare thoughtful questions about the team dynamics, ongoing projects, and how data science is shaping the future of banking at Starling. This will demonstrate your genuine interest in the role.

We think you need these skills to ace Data Scientist (FinCrime and Customer Identity) - DS-1 [HighSalary]

Data Science
Machine Learning
Python
SQL
Scikit-learn
TensorFlow
PyTorch
Data Wrangling
Data Visualization
Communication Skills
Software Development Life Cycle
Version Control (Git)
Production Deployment of ML Solutions
Anomaly Detection
Anti-Money Laundering
Transaction Monitoring
Collaboration with Technical and Non-Technical Teams

Some tips for your application 🫡

Understand the Company Culture: Before applying, take some time to understand Starling's mission and values. Highlight how your personal values align with theirs in your application.

Tailor Your CV: Make sure your CV reflects relevant experience in data science and machine learning, especially in areas like financial crime and anomaly detection. Use specific examples that demonstrate your skills in Python, SQL, and machine learning libraries.

Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss your passion for using technology to improve banking and how you can contribute to their mission of fixing banking.

Prepare for the Interview Process: Familiarize yourself with the interview stages outlined by Starling. Prepare questions to ask during the interview to show your curiosity and engagement with the company.

How to prepare for a job interview at Starling Bank

✨Show Your Passion for FinTech

Starling is all about fixing banking and using technology to improve people's financial lives. Make sure to express your enthusiasm for the fintech industry and how you can contribute to their mission.

✨Prepare for Technical Questions

Expect to dive deep into your data science knowledge, especially around machine learning models and tools like Python and SQL. Brush up on your experience with libraries such as Scikit-learn and Tensorflow, as well as your understanding of the software development life cycle.

✨Demonstrate Collaboration Skills

Starling values teamwork and collaboration. Be ready to discuss examples of how you've worked with both technical and non-technical teams in the past to deliver insights and solutions.

✨Ask Thoughtful Questions

Interviews at Starling are conversational, so come prepared with questions that show your curiosity about the company culture, the team you'll be working with, and how your role contributes to the bigger picture.

Data Scientist (FinCrime and Customer Identity) - DS-1 [HighSalary]
Starling Bank
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  • Data Scientist (FinCrime and Customer Identity) - DS-1 [HighSalary]

    London
    Full-Time
    43200 - 72000 £ / year (est.)

    Application deadline: 2027-01-29

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    Starling Bank

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