At a Glance
- Tasks: Solve real-world problems using AI and collaborate with a dynamic team.
- Company: Global recruitment specialist with a focus on innovation and collaboration.
- Benefits: Remote work flexibility, competitive salary, and opportunities for professional growth.
- Other info: Hybrid work model with excellent career advancement opportunities.
- Why this job: Join a cutting-edge team and make an impact in the world of data science.
- Qualifications: Experience in Python, machine learning, and strong communication skills.
The predicted salary is between 60000 - 80000 £ per year.
We are a Global Recruitment specialist that provides support to the clients across EMEA, APAC, US and Canada.
Location: London (Hybrid – 3 days per week onsite)
- 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 Science Data Science Senior Data Scientist (Remote) employer: eTeam
Contact Detail:
eTeam Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Data Science Senior Data Scientist (Remote)
✨Tip Number 1
Networking is key! Reach out to professionals in the data science field on LinkedIn or attend industry meetups. We can leverage our connections to get insights and maybe even a referral for that Senior Data Scientist role.
✨Tip Number 2
Prepare for interviews by practising common data science questions and case studies. We should also be ready to discuss our past projects and how they relate to the job description. Mock interviews with friends can help us nail it!
✨Tip Number 3
Showcase your skills through a portfolio. We can create a GitHub repository with our projects, especially those involving Python and ML algorithms. This gives potential employers a taste of what we can do!
✨Tip Number 4
Don’t forget to apply through our website! It’s a great way to ensure your application gets noticed. Plus, we can follow up directly with the hiring team to express our enthusiasm for the Senior Data Scientist position.
We think you need these skills to ace Data Science Data Science Senior Data Scientist (Remote)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Data Scientist role. Highlight your experience with Python, ML algorithms, and any relevant projects that showcase your skills in business understanding and data preprocessing.
Showcase Your Projects: Include specific examples of projects where you've worked on model selection, training, and deployment. This will help us see your hands-on experience and how you approach problem-solving in real-world scenarios.
Be Clear and Concise: When writing your application, keep it clear and concise. Use bullet points for easy reading and make sure to communicate your key achievements and skills effectively. We appreciate straightforwardness!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to hear from you!
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 experience with data acquisition and preprocessing, as well as any relevant KPIs. Being able to discuss specific examples will show that you understand the business problems and can translate them into technical solutions.
✨Showcase Your Model Mastery
Be prepared to talk about your experience with model selection and training. Highlight any projects where you’ve designed training strategies or worked with ML algorithms like BERT or GPT-3. Discuss how you evaluated model performance and optimised it, as this will demonstrate your technical expertise.
✨Collaboration is Key
Since this role involves working closely with ML engineers and product managers, be ready to share examples of successful collaborations. Talk about how you’ve communicated complex ideas to non-technical stakeholders and how you’ve contributed to team projects. This will show that you’re a team player who values collaboration.
✨Prepare for Technical Questions
Expect some technical questions during the interview, especially around deployment and monitoring of AI models. Brush up on your knowledge of automated monitoring systems and how to handle unexpected behaviour in models. Being able to answer these questions confidently will set you apart from other candidates.