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- Tasks: Create AI tools to revolutionise motor insurance claim analysis and enhance efficiency.
- Company: Innovative firm in Staffordshire focused on transforming the insurance sector.
- Benefits: Competitive salary, professional development, and hands-on experience with cutting-edge technology.
- Why this job: Join a dynamic team and make a real impact in the fast-paced world of AI and insurance.
- Qualifications: Experience in data science, machine learning, and a passion for problem-solving.
- Other info: Collaborative environment with opportunities for rapid learning and career growth.
The predicted salary is between 36000 - 60000 £ per year.
This post is a dynamic role that will develop bespoke AI-driven tools to automate motor insurance claim analysis, enhancing efficiency and accuracy. The KTP will embed advanced machine learning capabilities, reduce case turnaround times, and unlock scalable growth, transforming data handling in the UK's high-volume, fraud-prone motor insurance sector.
The position will be based at the company premises in Staffordshire (ST18) working across departmental teams to ensure the work is embedded effectively, delivering internal training and creating documentation to support long-term adoption.
Key ResponsibilitiesThis project presents a multifaceted challenge, offering substantial opportunities for technical, commercial, and professional development.
- You will be responsible for designing and implementing bespoke AI models, capable of extracting structured data from complex, unstructured legal documents.
- You will also need to manage multimodal datasets and ensure the models meet high standards of accuracy, fairness, and compliance.
- A key challenge will be understanding the complexity of the motor insurance industry, including the end-to-end process and navigating regulatory frameworks, requiring rapid learning and close collaboration with domain experts.
- To gain a deep understanding of Whichrate’s business goals, systems, and manual court pack analysis processes.
- Lead the requirements gathering and specification for an AI-driven claims analysis tool.
- Design and implement advanced machine learning and natural language processing models.
- Develop and deploy a functional Minimum Viable Product (MVP) for automated court pack analysis.
- Drive user training, change management, and knowledge transfer.
Data Scientist KTP Associate in Salford employer: University of Salford (Personnel)
Contact Detail:
University of Salford (Personnel) Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist KTP Associate in Salford
✨Tip Number 1
Network like a pro! Reach out to professionals in the motor insurance and AI sectors on LinkedIn. Join relevant groups and engage in discussions to get your name out there and learn about potential job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI models and data analysis projects. This will give you an edge during interviews, as you can demonstrate your hands-on experience and problem-solving abilities.
✨Tip Number 3
Prepare for those interviews! Research the company and its challenges in the motor insurance sector. Be ready to discuss how your skills can help them develop AI-driven tools and improve their processes.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might be perfect for you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Data Scientist KTP Associate in Salford
Some tips for your application 🫡
Show Your Passion for AI and Data: When writing your application, let us see your enthusiasm for AI and data science! Share any relevant projects or experiences that highlight your skills in machine learning and natural language processing. We love seeing candidates who are genuinely excited about transforming the motor insurance sector.
Tailor Your Application: Make sure to customise your application to fit the role of Data Scientist KTP Associate. Highlight your understanding of the motor insurance industry and how your background aligns with the responsibilities outlined in the job description. This shows us you’ve done your homework and are serious about the position!
Be Clear and Concise: Keep your application clear and to the point. Use straightforward language to explain your experiences and skills. We appreciate well-structured applications that make it easy for us to see why you’re a great fit for the role without wading through unnecessary fluff.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it gives you a chance to explore more about what we do at StudySmarter while you’re at it!
How to prepare for a job interview at University of Salford (Personnel)
✨Know Your AI and ML Stuff
Make sure you brush up on your knowledge of AI and machine learning concepts. Be ready to discuss specific algorithms you've worked with, especially in relation to natural language processing and data extraction from unstructured documents. This will show that you’re not just familiar with the theory but have practical experience too.
✨Understand the Motor Insurance Sector
Take some time to research the motor insurance industry, particularly the challenges it faces with fraud and data handling. Being able to speak intelligently about the sector will demonstrate your commitment and understanding of the role's context, which is crucial for success.
✨Prepare for Technical Questions
Expect technical questions that assess your problem-solving skills and your ability to design AI models. Practice explaining your thought process clearly and concisely, as this will help interviewers gauge your analytical skills and how you approach complex problems.
✨Showcase Your Collaboration Skills
Since this role involves working across departmental teams, be prepared to discuss examples of how you've successfully collaborated in the past. Highlight any experiences where you’ve led training sessions or created documentation, as these will be key aspects of the job.
