Data Scientist - Fintech ML for Growth & Risk in London

Data Scientist - Fintech ML for Growth & Risk in London

London Full-Time 50000 - 60000 £ / year (est.) No working from home possible
myPOS

At a Glance

  • Tasks: Build and maintain machine learning models to optimise decision-making in fintech.
  • Company: myPOS, a rapidly expanding payment solutions company based in Greater London.
  • Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
  • Why this job: Join us to transform the future of payments with innovative data science solutions.
  • Qualifications: 3-5 years of data science experience and proficiency in Python required.

The predicted salary is between 50000 - 60000 £ per year.

myPOS, based in Greater London, is seeking an experienced Data Scientist to support our rapidly expanding payment solutions. You will build and maintain machine learning models, optimize decision-making processes, and collaborate with diverse teams to drive impactful projects.

The ideal candidate will have 3-5 years of applied data science experience, proficiency in Python, and a solid understanding of machine learning methodologies. Join us in transforming the future of payments!

Data Scientist - Fintech ML for Growth & Risk in London employer: myPOS

myPOS is an exceptional employer located in the vibrant Greater London area, offering a dynamic work culture that fosters innovation and collaboration. Employees benefit from continuous growth opportunities, competitive compensation, and the chance to work on cutting-edge fintech projects that are transforming the payments landscape. Join us to be part of a forward-thinking team where your contributions will make a real impact.

myPOS

Contact Details:

myPOS Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Scientist - Fintech ML for Growth & Risk 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 myPOS!

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 Data Scientist - Fintech ML for Growth & Risk at myPOS.

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 myPOS.

Apply Directly through Our Website

When you find a suitable opening like Data Scientist - Fintech ML for Growth & Risk at myPOS, 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 Data Scientist - Fintech ML for Growth & Risk in London

Python
Problem-Solving Skills
SQL
Communication 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 myPOS, 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 myPOS. 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 myPOS

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 myPOS!

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.