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- Tasks: Build innovative models for credit risk insights using AI and NLP techniques.
- Company: Progressive credit referencing start-up in Greater London with a focus on diversity.
- Benefits: Remote work, collaborative culture, and opportunities for professional growth.
- Why this job: Join a dynamic team and make an impact in the fintech industry.
- Qualifications: Experience in Python and NLP techniques is essential.
- Other info: Perfect for ambitious individuals eager to advance their careers.
The predicted salary is between 36000 - 60000 £ per year.
A progressive credit referencing start-up in Greater London is seeking a hands-on Data Scientist to collaborate with the lead data scientist. This role involves building foundational Linear Regression models and developing advanced XGBoost models for risk insights.
Candidates should possess experience with NLP techniques and strong Python skills. The position is primarily remote with a commitment to diversity and collaboration. Ideal for ambitious individuals looking to grow in a dynamic environment.
Credit Risk Data Scientist: AI & NLP Innovator in London employer: Infact
Contact Detail:
Infact Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Credit Risk Data Scientist: AI & NLP Innovator in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the credit risk and data science fields on LinkedIn. Join relevant groups and participate in discussions to get your name out there and show off your passion for AI and NLP.
✨Tip Number 2
Showcase your skills! Create a portfolio of projects that highlight your experience with Linear Regression and XGBoost models. Share your work on platforms like GitHub, and don’t forget to include any NLP techniques you've mastered.
✨Tip Number 3
Prepare for interviews by brushing up on common data science questions and case studies. Practice explaining your thought process when building models, as well as how you approach problem-solving in a collaborative environment.
✨Tip Number 4
Apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to reflect your enthusiasm for the role and how you can contribute to our diverse and dynamic culture.
We think you need these skills to ace Credit Risk Data Scientist: AI & NLP Innovator in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with Python and NLP techniques in your application. We want to see how you can bring your skills to the table, so don’t hold back!
Tailor Your Application: Take a moment to customise your CV and cover letter for this role. Mention specific projects or experiences that relate to building Linear Regression and XGBoost models. It’ll show us you’re genuinely interested!
Be Yourself: We value diversity and collaboration, so let your personality shine through in your application. Share your passion for data science and how you envision contributing to our team.
Apply Through Our Website: For the best chance of getting noticed, make sure to apply directly through our website. It’s the quickest way for us to see your application and get the ball rolling!
How to prepare for a job interview at Infact
✨Know Your Models
Make sure you brush up on Linear Regression and XGBoost models before the interview. Be ready to discuss how you've used these techniques in past projects, as well as any challenges you faced and how you overcame them.
✨Show Off Your NLP Skills
Since the role requires experience with NLP techniques, prepare to talk about specific projects where you've implemented these methods. Bring examples of how your work has led to actionable insights, and be ready to explain your thought process.
✨Demonstrate Your Python Proficiency
Python is key for this position, so be prepared to showcase your coding skills. You might be asked to solve a problem on the spot, so practice common data manipulation tasks and be familiar with libraries like Pandas and Scikit-learn.
✨Embrace Collaboration and Diversity
This start-up values collaboration and diversity, so highlight your experiences working in diverse teams. Share examples of how you've contributed to a positive team environment and how you adapt your communication style to different audiences.
