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For Companies At a Glance
- Tasks: Develop and deliver innovative AI solutions for large-scale organisations.
- Company: Join a Tier 1 client known for cutting-edge technology and impactful projects.
- Benefits: Enjoy flexible work, 25 days leave, health insurance, and professional development opportunities.
- Why this job: Be at the forefront of AI technology while collaborating with diverse teams and clients.
- Qualifications: Strong data science background, experience in machine learning, and excellent communication skills required.
- Other info: Opportunities for international work and regular team socials to enhance your experience.
The predicted salary is between 43200 - 72000 £ per year.
Job Description
AI Engineer – Data Science
Hybrid | London, England | Engineering
Overview
The Explore Group are partnered with one of our Tier 1 clients to secure AI Engineers with strong data science expertise who are eager to develop and deliver innovative AI solutions for large scale organisations. This role requires a combination of technical skills and business understanding, working with advanced AI technologies to create impactful data driven applications.
Responsibilities
- Partner with enterprise clients to understand requirements and design tailored AI and data science solutions
- Apply statistical modelling, machine learning, and programming expertise to solve complex problems
- Explore and implement modern AI technologies including large language models, retrieval augmented generation, and advanced automation tools
- Deliver production ready solutions that integrate into existing client environments
- Engage with stakeholders at different levels, translating technical approaches into clear business outcomes
- Stay up to date with rapidly evolving AI tools and actively incorporate them into solution design
Requirements
- Strong background in data science and machine learning with solid understanding of statistics and programming
- Exposure to MLOps and experience deploying models into production environments
- Interest and practical experience in using emerging AI technologies such as co pilots, agentic frameworks, and generative AI applications
- Proven ability to manage client expectations and deliver high quality solutions in a collaborative environment
- Excellent communication skills with the ability to present technical concepts to both technical and non technical audiences
Benefits
We offer a supportive and flexible work environment with a comprehensive benefits package including:
- 25 days of annual leave plus bank holidays
- Share options and pension scheme
- Health and dental insurance options
- Professional learning and development budget
- Cycle to work scheme and technology allowance
- Referral bonus scheme
- Opportunities to work abroad for limited periods
- Regular team socials and office perks
AI Engineer - Data Science employer: Explore Group
Contact Detail:
Explore Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer - Data Science
✨Tip Number 1
Familiarise yourself with the latest AI technologies mentioned in the job description, such as large language models and generative AI applications. Being able to discuss these technologies confidently during interviews will show your enthusiasm and readiness for the role.
✨Tip Number 2
Prepare examples of past projects where you've applied machine learning and data science techniques. Be ready to explain how you approached complex problems and the impact your solutions had on previous clients or organisations.
✨Tip Number 3
Practice translating technical concepts into business outcomes. This is crucial for engaging with stakeholders at different levels, so consider how you can simplify complex ideas and demonstrate their value to non-technical audiences.
✨Tip Number 4
Network with professionals in the AI and data science fields. Attend relevant meetups or webinars to connect with others in the industry, which could lead to valuable insights and potential referrals for the position.
We think you need these skills to ace AI Engineer - Data Science
Some tips for your application 🫡
Understand the Role: Before applying, make sure to thoroughly read the job description for the AI Engineer - Data Science position. Understand the key responsibilities and requirements, and think about how your skills align with them.
Tailor Your CV: Customise your CV to highlight relevant experience in data science, machine learning, and AI technologies. Use specific examples that demonstrate your expertise and how you've successfully delivered solutions in previous roles.
Craft a Compelling Cover Letter: Write a cover letter that not only showcases your technical skills but also your understanding of business needs. Explain how you can translate complex AI concepts into actionable business outcomes for clients.
Showcase Continuous Learning: Mention any recent courses, certifications, or projects related to emerging AI technologies. This shows your commitment to staying updated in a rapidly evolving field, which is crucial for the role.
How to prepare for a job interview at Explore Group
✨Showcase Your Technical Skills
Be prepared to discuss your experience with data science and machine learning. Highlight specific projects where you've applied statistical modelling and programming to solve complex problems, as this will demonstrate your technical expertise.
✨Understand the Business Context
Make sure you can articulate how your technical skills translate into business outcomes. Research the company and its clients to understand their needs, and be ready to discuss how your solutions can address those requirements.
✨Familiarise Yourself with Emerging AI Technologies
Since the role involves working with modern AI technologies, brush up on topics like large language models and generative AI applications. Being able to discuss these technologies confidently will show your enthusiasm and readiness for the role.
✨Practice Clear Communication
You’ll need to explain complex technical concepts to both technical and non-technical stakeholders. Practise simplifying your explanations and using relatable examples to ensure your ideas are easily understood.
