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- Tasks: Join our team to deliver data-driven solutions and insights that transform banking.
- Company: Starling is the UK's leading digital bank, revolutionizing how people manage their money.
- Benefits: Enjoy 25 days holiday, private medical insurance, and a flexible work environment.
- Why this job: Be part of a fast-paced, innovative culture that values collaboration and creativity.
- Qualifications: No specific experience required; we value aptitude and attitude over qualifications.
- Other info: We embrace diversity and encourage applicants from all backgrounds to apply.
The predicted salary is between 36000 - 60000 £ 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 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.
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:
- 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
Requirements
We’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
Desirables:
- Experience with AWS/GCP
- Desire to build explainable ML models (using techniques such as SHAP)
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 – 90 mins technical interview with two team members
- Stage 4 – 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 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.
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.
Seniority level
- Entry level
Employment type
- Full-time
Job function
- Engineering and Information Technology
- Industries
- IT Services and IT Consulting
#J-18808-Ljbffr
Data Scientist (Fincrime) employer: Starling Bank
Contact Detail:
Starling Bank Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist (Fincrime)
✨Tip Number 1
Familiarize yourself with the specific technologies and tools mentioned in the job description, such as Python, SQL, and machine learning libraries like Scikit-learn and Tensorflow. Being able to discuss your experience with these tools during the interview will show that you're a strong fit for the role.
✨Tip Number 2
Engage with the Starling community by reading their blogs or case studies, especially those related to data science and financial crime. This will not only give you insights into their work culture but also help you formulate relevant questions to ask during your interview.
✨Tip Number 3
Prepare to demonstrate your problem-solving skills through practical examples. Think of scenarios where you've successfully applied data science techniques to solve real-world problems, particularly in financial contexts, as this aligns closely with the responsibilities of the role.
✨Tip Number 4
Show your enthusiasm for innovation and collaboration, which are key values at Starling. Be ready to discuss how you've worked in teams to drive projects forward and how you can contribute to their mission of reshaping banking.
We think you need these skills to ace Data Scientist (Fincrime)
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 financial crime. 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.
Prepare for the Interview Process: Familiarize yourself with the interview stages outlined in the job description. Prepare questions to ask during the interviews to show your curiosity and engagement with the role and the company.
How to prepare for a job interview at Starling Bank
✨Show Your Passion for Fintech
Make sure to express your enthusiasm for the fintech industry and how it aligns with Starling's mission to transform banking. Share any personal experiences or projects that demonstrate your commitment to innovation in financial services.
✨Prepare for Technical Questions
Expect technical questions related to data science and machine learning, especially in the context of financial crime. Brush up on your knowledge of Python, SQL, and relevant libraries like Scikit-learn and Tensorflow, and be ready to discuss your experience deploying ML models.
✨Ask Insightful Questions
Interviews at Starling are conversational, so come prepared with thoughtful questions about the team, projects, and company culture. This shows your genuine interest and helps you assess if Starling is the right fit for you.
✨Demonstrate Ownership and Initiative
Starling values self-driven individuals who take ownership of their work. Be ready to share examples of how you've proactively solved problems or improved processes in previous roles, showcasing your ability to contribute positively to the team.
