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For Companies At a Glance
- Tasks: Lead machine-learning initiatives and develop cutting-edge AI solutions.
- Company: Join a pioneering AI platform transforming customer service with speed and accuracy.
- Benefits: Remote work, competitive salary, and opportunities for professional growth.
- Why this job: Be at the forefront of AI technology and tackle real-world challenges.
- Qualifications: 6 years in data science, with strong skills in computer vision and ML pipelines.
- Other info: Dynamic team environment with a focus on innovation and collaboration.
The predicted salary is between 48000 - 72000 £ per year.
Our client is building the most advanced AI platform in their market. They help their clients serve customers with unmatched speed and accuracy. They’ve invested heavily into building the ML stack, partnered with leading universities, and trained models on millions of expert-tagged images. Now, they are scaling globally and need a world-class Lead Data Scientist to help push the boundaries of computer vision, video analysis, and multimodal LLMs while solving real-world challenges.
Role Overview
They are looking for an experienced Lead Data Scientist to spearhead machine-learning initiatives, with particular focus on computer vision, large language models, and production-ready ML pipelines in Azure. You will act as the technical lead for the team, setting direction, guiding best practices, and ensuring the successful delivery of high-impact AI solutions.
Key Responsibilities
- Develop, train, and deploy computer vision models (object detection, image classification, segmentation, multi-modal learning).
- Fine-tune, evaluate, and productionise multi-modal LLMs for business applications.
- Drive experimentation and prototyping of advanced ML/AI techniques.
- Provide technical direction, mentoring, and hands-on guidance to the data science team.
- Work with engineering, product, and business stakeholders to align ML strategy with business goals.
- Architect and productionise end-to-end ML pipelines on Azure, while ensuring scalability, reproducibility, and monitoring of deployed models.
Requirements
- 6 years in data science/ML, with at least 2 years in a technical lead role.
- Deep experience in training and deploying computer vision models into production.
- Proven track record with LLM fine-tuning, prompt engineering, and productionisation.
- Deep experience in MLOps on Azure, including CI/CD, monitoring, and scaling pipelines.
- Strong coding skills in Python, with frameworks such as PyTorch, FastAPI, and Azure CLI.
ALL APPLICANTS MUST BE FREE TO WORK IN THE UK.
Locations
Lead Data Scientist - Remote in Midlothian, Newbridge, Scotland employer: Exposed Solutions
Contact Detail:
Exposed Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist - Remote in Midlothian, Newbridge, Scotland
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field, especially those who might know someone at the company you're eyeing. A friendly chat can sometimes lead to a referral, which is gold when it comes to landing that interview.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best projects, especially those related to computer vision and ML pipelines. Share it on platforms like GitHub or even your own website, and don’t forget to link it in your applications!
✨Tip Number 3
Prepare for the technical grill! Brush up on your coding skills in Python and be ready to discuss your experience with Azure and ML models. Practising common data science interview questions can help you feel more confident when the time comes.
✨Tip Number 4
Apply through our website! We make it super easy for you to submit your application directly. Plus, it shows you're genuinely interested in the role and the company, which can set you apart from the crowd.
We think you need these skills to ace Lead Data Scientist - Remote in Midlothian, Newbridge, Scotland
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Lead Data Scientist role. Highlight your experience with computer vision, large language models, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how you can contribute to our mission. Be sure to mention specific experiences that relate to the key responsibilities outlined in the job description.
Showcase Your Technical Skills: Don’t forget to highlight your coding skills in Python and your experience with Azure ML pipelines. We love seeing practical examples of your work, so if you have any projects or GitHub repositories, include them in your application!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it makes the process smoother for everyone involved!
How to prepare for a job interview at Exposed Solutions
✨Know Your Stuff
Make sure you brush up on your knowledge of computer vision and large language models. Be ready to discuss your experience with training and deploying models, especially in Azure. The more specific examples you can provide, the better!
✨Showcase Your Leadership Skills
As a Lead Data Scientist, you'll need to demonstrate your ability to guide a team. Prepare to share instances where you've provided technical direction or mentored others. Highlight how you’ve driven successful machine-learning initiatives in the past.
✨Align with Business Goals
Understand how machine learning strategies can align with business objectives. Be prepared to discuss how you've collaborated with engineering and product teams to ensure that your ML solutions meet real-world challenges and business needs.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company's AI platform and their future goals. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
