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- Tasks: Own and optimise ML models for consumer lending in a dynamic environment.
- Company: Major financial services group focused on innovation in the South West UK.
- Benefits: Strong salary, hybrid work model, and opportunities for professional growth.
- Why this job: Make a real impact in consumer lending with cutting-edge machine learning techniques.
- Qualifications: Solid Python and SQL skills, plus experience with statistics and real-world datasets.
- Other info: Join a collaborative team dedicated to innovation and career development.
The predicted salary is between 36000 - 60000 £ per year.
A major financial services group in the South West UK seeks a Data Scientist specializing in Machine Learning and Consumer Lending. This hybrid role offers a strong salary depending on experience and involves end-to-end ownership of ML models in production.
The ideal candidate will possess:
- Solid Python and SQL skills
- Experience with statistics and real-world datasets
- Insight into using ML for consumer lending improvement
Join a dynamic team dedicated to innovation and growth.
Credit Card ML Data Scientist – Hybrid UK in Edinburgh employer: Datatech Analytics
Contact Detail:
Datatech Analytics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Credit Card ML Data Scientist – Hybrid UK in Edinburgh
✨Tip Number 1
Network like a pro! Reach out to current employees in the financial services sector, especially those working with ML and data science. A friendly chat can give us insider info and might even lead to a referral!
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your best ML projects, especially those related to consumer lending. We want to see how you’ve tackled real-world datasets and applied Python and SQL in your work.
✨Tip Number 3
Ace the interview! Brush up on your statistics and be ready to discuss how you've used ML to drive improvements in consumer lending. We love candidates who can think critically and share their insights.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we’re always on the lookout for passionate individuals ready to join our dynamic team.
We think you need these skills to ace Credit Card ML Data Scientist – Hybrid UK in Edinburgh
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your Python and SQL skills in your application. We want to see how you've used these tools in real-world projects, especially in the context of machine learning and consumer lending.
Be Specific About Your Experience: When detailing your experience, focus on specific ML models you've worked on and the impact they had. We love seeing candidates who can demonstrate end-to-end ownership of their projects!
Tailor Your Application: Don’t just send a generic CV and cover letter. Tailor your application to reflect the job description. Mention how your background aligns with our goals in innovation and growth in the financial services sector.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Datatech Analytics
✨Know Your ML Models
Make sure you can discuss various machine learning models and their applications in consumer lending. Be prepared to explain how you've used these models in past projects, especially in terms of improving outcomes.
✨Brush Up on Python and SQL
Since solid Python and SQL skills are a must, review your coding practices and be ready to solve problems on the spot. Practising common data manipulation tasks can really help you shine during technical discussions.
✨Showcase Your Statistical Knowledge
Be ready to talk about statistical methods you've applied in real-world datasets. Highlight any experience with A/B testing or predictive analytics, as this will demonstrate your ability to derive insights from data.
✨Demonstrate Your Passion for Innovation
This role is all about being part of a dynamic team focused on growth. Share examples of how you've contributed to innovative projects in the past, and express your enthusiasm for staying ahead in the rapidly evolving field of machine learning.
