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- Tasks: Develop credit risk models and scorecards for a long-term finance project.
- Company: Join Opus Recruitment Solutions, a leader in connecting talent with opportunities.
- Benefits: Enjoy remote work flexibility and competitive daily rates between £400 and £500.
- Why this job: Make an impact in the finance sector while honing your data science skills.
- Qualifications: Experience in Python, R, SAS, SPSS, and credit scorecard development required.
- Other info: This is a contract role lasting 12-24 months, outside IR35.
This is a contract role based in London, UK, paying between £400 and £500 per day. The position involves developing credit risk models and scorecards for a long-term project in the finance sector. The role is primarily remote with occasional travel, outside IR35, for 12 to 24 months.
Key Requirements
- Extensive experience in Python and R
- Strong experience with SAS and SPSS
- Previous experience in credit scorecard development
- Strong statistical background
- Proficiency with Jupyter Notebook
- Finance industry experience
- Proven track record in mentoring and training team members
If you are interested and meet these requirements, please apply with your most recent CV.
Additional Notes
Please note that applicants without a passport for the country of the vacancy may need a work permit. For more information, visit our blog. Do not provide bank or payment details when applying. All applications should be submitted via the 'Apply now' button.
Data Scientist (Credit Risk) | 12-24 Months | £400 - £500 | Outside IR35 | Remote First employer: Job Traffic
Contact Detail:
Job Traffic Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist (Credit Risk) | 12-24 Months | £400 - £500 | Outside IR35 | Remote First
✨Tip Number 1
Make sure to highlight your experience with Python and R in your conversations. These are crucial skills for the role, and demonstrating your proficiency can set you apart from other candidates.
✨Tip Number 2
Familiarise yourself with credit risk models and scorecard development. Being able to discuss specific projects or methodologies you've used in the past will show your expertise and confidence in this area.
✨Tip Number 3
If you have experience mentoring or training others, be prepared to share examples. This is a valuable asset for the role, and showcasing your leadership skills can make a strong impression.
✨Tip Number 4
Since the role is remote-first, emphasise your ability to work independently and manage your time effectively. Discuss any previous remote work experiences to demonstrate your adaptability.
We think you need these skills to ace Data Scientist (Credit Risk) | 12-24 Months | £400 - £500 | Outside IR35 | Remote First
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your extensive experience in Python, R, SAS, and SPSS. Include specific examples of credit scorecard development and any relevant projects in the finance sector.
Showcase Your Skills: In your application, emphasise your strong statistical background and proficiency with Jupyter Notebook. Mention any mentoring or training experience to demonstrate your leadership capabilities.
Write a Compelling Cover Letter: Craft a cover letter that connects your skills and experiences directly to the job requirements. Explain why you are interested in this role and how you can contribute to the company's success in credit risk modelling.
Follow Application Instructions: Ensure you apply through the 'Apply now' button as specified. Double-check that you have included all necessary documents and that your application is free from errors before submission.
How to prepare for a job interview at Job Traffic
✨Showcase Your Technical Skills
Make sure to highlight your extensive experience in Python and R during the interview. Be prepared to discuss specific projects where you've developed credit risk models or scorecards, as this will demonstrate your practical knowledge and expertise.
✨Discuss Your Statistical Background
Since a strong statistical background is crucial for this role, be ready to explain complex statistical concepts in simple terms. You might also want to prepare examples of how you've applied these concepts in real-world scenarios, particularly in credit risk.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills in credit risk situations. Think about past experiences where you had to make data-driven decisions and be ready to walk the interviewer through your thought process.
✨Emphasise Mentoring Experience
Since the role requires mentoring and training team members, be sure to share your experiences in this area. Discuss how you've successfully guided others in their professional development, and what strategies you used to foster a collaborative learning environment.
