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- 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 a vibrant London office with excellent career advancement opportunities.
- Why this job: Join a dynamic team and make an impact in the world of AI and data science.
- Qualifications: Experience in Python, machine learning, and 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.
Marketing Data Scientist in London employer: eTeam
Contact Detail:
eTeam Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Marketing Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python and machine learning. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions related to data science and be ready to discuss your past experiences and how they relate to the role.
✨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 Marketing Data Scientist in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Marketing Data Scientist role. Highlight your experience with Python, ML algorithms, and any relevant projects that showcase your skills in data acquisition and model training.
Showcase Your Collaboration Skills: Since collaboration is key in this role, mention any past experiences where you worked with cross-functional teams. This could be with ML engineers, product managers, or domain experts—let us know how you contributed!
Be Clear and Concise: When writing your application, keep it clear and concise. Use bullet points for easy reading and make sure to directly address the key responsibilities mentioned in the job description.
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 updates from us!
How to prepare for a job interview at eTeam
✨Know Your Data Inside Out
Make sure you understand the data sources relevant to the role. Be prepared to discuss how you would approach data acquisition and preprocessing, as well as the importance of data quality in your projects.
✨Brush Up on Your ML Algorithms
Familiarise yourself with various machine learning algorithms, especially those mentioned in the job description like LLM architectures. Be ready to explain why you would choose a specific algorithm for a given business problem.
✨Prepare for Technical Questions
Expect questions about model evaluation metrics such as accuracy, precision, recall, and F1-score. Have examples ready that demonstrate how you've used these metrics in past projects to optimise model performance.
✨Showcase Your Collaboration Skills
Since collaboration is key in this role, think of examples where you've worked with cross-functional teams. Highlight your communication skills and how you’ve effectively collaborated with engineers and product managers in previous roles.