Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Develop AI models and collaborate with teams to solve real business problems.
- Company: Global recruitment specialist with a focus on innovation and collaboration.
- Benefits: Competitive pay, flexible work environment, and opportunities for professional growth.
- Other info: Work in London with a hybrid model, fostering a collaborative culture.
- Why this job: Join a dynamic team and make an impact in the world of data science.
- Qualifications: Experience in Python and machine learning; strong communication skills.
The predicted salary is between 30000 - 40000 £ per year.
We are a Global Recruitment specialist that provides support to the clients across EMEA, APAC, US and Canada.
Location: London (3 days office)
Pay-rate: £401 per day (PAYE through Umbrella)
- 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. Design and select appropriate ML algorithms and architecture (LLM architecture, e.g., BERT, GPT-3) based on project requirements. 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. 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.
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.
Data Marketing Scientist in London employer: eTeam
Contact Detail:
eTeam Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Marketing Scientist in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry on LinkedIn or at events. 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 Python and ML. 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 practising common data science questions and case studies. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love hearing from passionate candidates who are eager to join our team!
We think you need these skills to ace Data Marketing Scientist in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Data Marketing Scientist. Highlight your experience with Python, data acquisition, and model training. We want to see how your skills align with our needs!
Showcase Your Projects: Include specific projects where you've tackled business problems using AI models. We love seeing real-world applications of your skills, so don’t hold back on the details!
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language to describe your experience and how it relates to the job. We appreciate a well-structured application that gets to the point!
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 any important updates from us!
How to prepare for a job interview at eTeam
✨Know Your Data Inside Out
Before the interview, make sure you’re familiar with the types of data you’ll be working with. Brush up on your Python skills and understand how to translate business problems into technical specifications. Being able to discuss specific data sources and KPIs will show that you’re ready to hit the ground running.
✨Showcase Your Model Mastery
Be prepared to talk about your experience with different ML algorithms and architectures, especially LLMs like BERT and GPT-3. Have examples ready where you’ve designed training strategies or optimised models. This will demonstrate your hands-on experience and understanding of model performance metrics.
✨Collaboration is Key
Highlight your teamwork skills during the interview. Discuss how you’ve collaborated with ML engineers, product managers, and domain experts in the past. Companies want to see that you can communicate effectively and work well within a team to achieve common goals.
✨Prepare for Real-World Scenarios
Expect to tackle hypothetical scenarios related to data acquisition, preprocessing, and model deployment. Practise explaining your thought process and decision-making in these situations. This will help you convey your problem-solving skills and adaptability, which are crucial for the role.