Hybrid Data Scientist - FinTech ML & Impact in London

Hybrid Data Scientist - FinTech ML & Impact in London

London Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
Kroo Bank

At a Glance

  • Tasks: Enhance decision-making through data science and develop models for credit risk and fraud prevention.
  • Company: Kroo Bank, a dynamic fintech company focused on innovation.
  • Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
  • Other info: Collaborate with diverse teams in a fast-paced environment.
  • Why this job: Make a real impact in fintech while working with cutting-edge machine learning technologies.
  • Qualifications: Experience in machine learning, Python, and strong analytical skills.

The predicted salary is between 60000 - 80000 £ per year.

Kroo Bank is seeking a Data Scientist to enhance decision-making through data science. You'll work on models for credit risk, fraud prevention, and customer engagement.

The role allows hybrid work, requiring 1-2 days in the London office weekly. Ideal candidates have experience in machine learning, Python, and strong analytical skills.

Contribute to high-quality data practices while collaborating with multiple teams in a fast-paced fintech environment.

Hybrid Data Scientist - FinTech ML & Impact in London employer: Kroo Bank

Kroo Bank is an exceptional employer that fosters a dynamic and inclusive work culture, where innovation thrives and employees are empowered to make impactful contributions. With a strong focus on professional development, team collaboration, and the flexibility of hybrid working arrangements, Kroo Bank offers a unique opportunity for Data Scientists to grow their careers in the vibrant fintech sector of London, all while making a meaningful difference in the financial landscape.

Kroo Bank

Contact Details:

Kroo Bank Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Hybrid Data Scientist - FinTech ML & Impact in London

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Kroo Bank!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Hybrid Data Scientist - FinTech ML & Impact at Kroo Bank.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Kroo Bank.

Apply Directly through Our Website

When you find a suitable opening like Hybrid Data Scientist - FinTech ML & Impact at Kroo Bank, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Hybrid Data Scientist - FinTech ML & Impact in London

Communication Skills
Python
Problem-Solving Skills
SQL
Attention to Detail
Analytical Skills
Automation

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Kroo Bank, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Kroo Bank. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Kroo Bank

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Kroo Bank!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.