At a Glance
- Tasks: Build and enhance machine learning models for credit, fraud, and pricing.
- Company: Fast-growing fintech based in London with a focus on innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Collaborate with stakeholders to deliver data-driven insights and support AI initiatives.
- Why this job: Join a dynamic team and make an impact in the fintech industry.
- Qualifications: 1-2 years of Data Science experience, strong Python and SQL skills.
The predicted salary is between 45000 - 55000 £ per year.
A fast-growing London-based fintech is hiring a Data Scientist to help build and enhance machine learning models across credit, fraud and pricing.
The opportunity
- Build and improve ML models for decisioning and analytics
- Support model deployment and performance monitoring
- Partner with stakeholders to deliver data-driven insights
- Support the development and implementation of the company's wider AI roadmap
Your background
- c.1-2 years of experience in Data Science within financial services or fintech
- Strong Python and SQL skills
- Experience applying machine learning in a commercial environment
- Ability to communicate insights clearly to non-technical stakeholders
- Ideally exposure to modelling in credit, fraud or pricing
Data Scientist employer: Kinarden Search
Join a dynamic and innovative fintech in London, where your contributions as a Data Scientist will directly impact the development of cutting-edge machine learning models. With a strong emphasis on collaboration and professional growth, the company offers a vibrant work culture, competitive benefits, and opportunities to advance your career in the fast-evolving financial technology sector. Experience the unique advantage of working in a city renowned for its financial services, while being part of a team that values data-driven insights and creativity.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the fintech space, especially those working in data science. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to credit, fraud, or pricing. This will help you stand out when we’re looking for someone with practical experience.
✨Tip Number 3
Prepare for interviews by brushing up on your Python and SQL skills. We love candidates who can demonstrate their technical prowess while also explaining complex concepts in simple terms to non-techies.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in Data Science, especially within financial services or fintech. We want to see how your skills in Python and SQL can shine through!
Showcase Your Projects:Include specific examples of machine learning models you've built or improved. We love seeing real-world applications, so don’t hold back on the details!
Communicate Clearly:Remember, you’ll need to explain complex insights to non-technical stakeholders. Use simple language in your application to demonstrate your ability to communicate effectively.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and get to know you better!
How to prepare for a job interview at Kinarden Search
✨Know Your ML Models
Make sure you brush up on the machine learning models you've worked with, especially in credit, fraud, and pricing. Be ready to discuss specific projects where you applied these models and the impact they had. This shows your practical experience and understanding of the field.
✨Show Off Your Python and SQL Skills
Prepare to demonstrate your coding skills during the interview. You might be asked to solve a problem or explain how you would approach a data-related task using Python or SQL. Practising common data manipulation tasks can help you feel more confident.
✨Communicate Like a Pro
Since you'll need to share insights with non-technical stakeholders, practice explaining complex concepts in simple terms. Think about how you can convey your findings clearly and effectively, perhaps by using relatable examples or visuals.
✨Engage with Stakeholders
Be prepared to discuss how you've partnered with different teams in the past. Highlight any experiences where you gathered requirements or collaborated on projects. This will show that you understand the importance of teamwork in delivering data-driven insights.
