Impactful Data Scientist for FinTech Lending β€” Hybrid in London

Impactful Data Scientist for FinTech Lending β€” Hybrid in London

London Full-Time 60750 - 74250 Β£ / year (est.) Home office (partial)
Funding Circle

At a Glance

  • Tasks: Develop and implement cutting-edge models to drive value in FinTech lending.
  • Company: Join Funding Circle, a leading FinTech company in London.
  • Benefits: Enjoy a hybrid work model, competitive salary, and professional growth opportunities.
  • Other info: Be part of a dynamic team with exciting career advancement potential.
  • Why this job: Make a real impact by pushing AI boundaries and improving borrower products.
  • Qualifications: Experience in data science and strong collaboration skills required.

The predicted salary is between 60750 - 74250 Β£ per year.

Funding Circle in London is seeking a Data Scientist to join us as we evolve and build our next generation of models.

You will play a key role in developing, implementing and monitoring these models and drive significant value for the business.

You will work with data engineers, analysts, and business stakeholders to push the boundaries of AI, improve borrower products, and deliver real-time insights that guide decision making.

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Impactful Data Scientist for FinTech Lending β€” Hybrid in London employer: Funding Circle

Funding Circle is an exceptional employer that fosters a collaborative and innovative work culture, particularly in our London office where hybrid working allows for flexibility and balance. We prioritise employee growth through mentorship opportunities and encourage the development of cutting-edge AI solutions, all while offering a competitive salary and comprehensive benefits that support your well-being and career advancement.

Funding Circle

Contact Details:

Funding Circle Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land Impactful Data Scientist for FinTech Lending β€” Hybrid 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 Funding Circle!

✨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 Impactful Data Scientist for FinTech Lending β€” Hybrid at Funding Circle.

✨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 Funding Circle.

✨Apply Directly through Our Website

When you find a suitable opening like Impactful Data Scientist for FinTech Lending β€” Hybrid at Funding Circle, 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 Impactful Data Scientist for FinTech Lending β€” Hybrid in London

Python
Communication Skills
SQL
Problem-Solving Skills
Automation
Data Engineering
Attention to Detail

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 Funding Circle, 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 Funding Circle. 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 Funding Circle

✨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 Funding Circle!

✨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.