Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead AI projects, design models, and optimise performance for impactful solutions.
- Company: Global recruitment specialist with a focus on innovation and collaboration.
- Benefits: Competitive daily rate, hybrid work model, and opportunities for professional growth.
- Other info: Exciting role with quick candidate feedback and potential for career advancement.
- Why this job: Join a dynamic team and shape the future of AI in a thriving environment.
- Qualifications: 8+ years in data science, expertise in GenAI, Python, and Azure.
The predicted salary is between 100000 - 120000 £ per year.
We are a Global Recruitment specialist that provides support to clients across EMEA, APAC, US and Canada. We have an excellent job opportunity for you.
Location: London (Hybrid – 3 days per week onsite)
Duration: 12 months
Rate range: GBP 454/day
Required Core Skills:
- GenAI
- Python
- Azure
Nice to have skills:
- Insurance industry experience
Minimum years of experience: 8+ years of experience
Responsibilities:
- Business Understanding and Scope Definition: Work with stakeholders to understand the business problem that the AI model aims to solve. Help define the project scope, translating business requirements into technical specifications, identify relevant data sources and determine key performance indicators (KPIs).
- Data Acquisition and Preprocessing: Work with ML engineers in designing pipelines collecting appropriate data from various sources, cleaning and preprocessing the data, and ensuring data quality.
- Model Selection and Training: Design appropriate training strategies (e.g., supervised learning, reinforcement learning) and configure model parameters. Design and select appropriate ML algorithms and architecture (LLM architecture (e.g., BERT, GPT-3) based on project requirements).
- Evaluation and Optimization: Recommend the metrics and design reports used to evaluate the model’s performance using various metrics, such as accuracy, precision, recall, and F1-score. Identify areas for improvement and optimize the model by adjusting parameters, trying different architectures, or incorporating new data.
- Prompt Engineering and Interaction Design: Designing prompts that effectively communicate with the LLM and elicit the desired responses. Phrase prompts to get the best results and avoid unintended consequences. Experiment with different prompts and evaluate their impact on the LLM's performance.
- Deployment and Monitoring: Work with Engineers to deploy the AI model into a production environment. Recommend the metrics and reports to be used to track model performance. Contribute to the setting up of automated monitoring systems and developing strategies for handling unexpected behaviour.
- Collaboration and Communication: Collaborate with other team members, including ML engineers, product managers, and domain experts. Communicate findings and recommendations to stakeholders.
If you are interested in this position and would like to learn more, please send through your CV and we will get in touch with you as soon as possible. Please note, candidates are often shortlisted within 48 hours.
Senior Data Scientist in Slough employer: eTeam
Contact Detail:
eTeam Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist in Slough
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field, especially those who work in companies you're interested in. A friendly chat can sometimes lead to job opportunities that aren't even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving GenAI and Python. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with stakeholders and team members.
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find roles that match your skills and experience. Plus, we often shortlist candidates within 48 hours, so you won't be left waiting around.
We think you need these skills to ace Senior Data Scientist in Slough
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Data Scientist role. Highlight your experience with GenAI, Python, and Azure, and don’t forget to mention any relevant projects that showcase your skills in model selection and training.
Showcase Your Experience: With 8+ years of experience required, we want to see how you've tackled business problems in the past. Use specific examples to demonstrate your understanding of data acquisition, preprocessing, and model evaluation.
Be Clear and Concise: When writing your application, clarity is key! Use straightforward language to explain your technical skills and experiences. Avoid jargon unless it’s necessary, and make sure your points are easy to follow.
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’re considered quickly. Plus, we often shortlist candidates within 48 hours!
How to prepare for a job interview at eTeam
✨Know Your Tech Inside Out
Make sure you’re well-versed in GenAI, Python, and Azure. Brush up on the latest trends and best practices in these areas, as you’ll likely be asked to demonstrate your knowledge during the interview. Prepare examples of how you've used these technologies in past projects.
✨Understand the Business Context
Since the role involves working closely with stakeholders, it’s crucial to understand the business problems that AI models can solve. Research the company’s industry and think about how your skills can address specific challenges they face, especially if you have experience in the insurance sector.
✨Prepare for Technical Questions
Expect to dive deep into model selection, training strategies, and evaluation metrics. Be ready to discuss your approach to designing ML algorithms and architectures, like LLMs. Practise explaining complex concepts in simple terms, as communication is key in this role.
✨Showcase Your Collaboration Skills
This position requires a lot of teamwork, so be prepared to discuss how you’ve collaborated with ML engineers, product managers, and other stakeholders in the past. Share specific examples of successful projects where effective communication made a difference.