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- Tasks: Develop predictive models and manage complex analytics projects to drive data-driven decisions.
- Company: Leading analytics firm in Greater London with a focus on innovation.
- Benefits: Competitive salary, excellent benefits, and opportunities for professional growth.
- Why this job: Join a dynamic team and make an impact in the world of data science and AI.
- Qualifications: BSc in a STEM field, strong analytical skills, and proficiency in Python and SQL.
- Other info: Collaborative environment with a commitment to innovation in data science.
The predicted salary is between 36000 - 60000 £ per year.
A leading analytics firm in Greater London is seeking a Data Scientist to join its Product Analytics & Innovation team. The successful candidate will enable data-driven decisions, develop predictive models, and manage complex analytics projects while collaborating with internal clients.
Ideal applicants should have:
- A BSc in a STEM field
- Extensive analytical experience
- Advanced programming skills in Python and SQL
A commitment to innovation in data science and machine learning is also desired. Competitive salary and excellent benefits offered.
Credit Risk Data Scientist: Lending Models & AI in London employer: Kount
Contact Detail:
Kount Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Credit Risk Data Scientist: Lending Models & AI in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at the firm. A personal introduction can make all the difference when you're applying for that Data Scientist role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your predictive models and analytics projects. This is your chance to demonstrate your advanced programming skills in Python and SQL, so make it shine!
✨Tip Number 3
Prepare for the interview by brushing up on your knowledge of machine learning and data science innovations. Be ready to discuss how you can enable data-driven decisions and manage complex analytics projects.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Credit Risk Data Scientist: Lending Models & AI in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your analytical experience and programming skills in Python and SQL. We want to see how your background aligns with the role of a Data Scientist in our Product Analytics & Innovation team.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us about your passion for data science and machine learning, and how you can contribute to our innovative projects. Keep it engaging and relevant to the job description.
Showcase Your Projects: If you've worked on any predictive models or complex analytics projects, make sure to mention them! We love seeing real examples of your work that demonstrate your skills and commitment to data-driven decisions.
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 ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Kount
✨Know Your Data Science Fundamentals
Brush up on your knowledge of predictive modelling and machine learning techniques. Be ready to discuss how you've applied these concepts in previous projects, especially in relation to lending models.
✨Show Off Your Programming Skills
Prepare to demonstrate your proficiency in Python and SQL. You might be asked to solve a coding problem or explain your approach to data manipulation, so practice common tasks and be ready to articulate your thought process.
✨Understand the Business Context
Research the analytics firm and its role in the lending industry. Be prepared to discuss how your work can drive data-driven decisions and improve their products. This shows that you’re not just a techie but also understand the business side of things.
✨Collaborate and Communicate
Since the role involves working with internal clients, think about examples where you've successfully collaborated on complex projects. Highlight your communication skills and how you’ve translated technical findings into actionable insights for non-technical stakeholders.
