At a Glance
- Tasks: Design, build, and deploy impactful AI/ML models for a cutting-edge platform.
- Company: Fast-growing tech company revolutionising data workflows.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Collaborate closely with leadership and engineers in a high-growth setting.
- Why this job: Make a real difference with your AI skills in a dynamic environment.
- Qualifications: Experience in AI/ML model deployment and strong Python skills required.
The predicted salary is between 50000 - 70000 € per year.
Location: Belfast (Hybrid)
Eligibility: UK work authorisation required (no sponsorship available)
I'm working with a fast-growing technology company building a platform that automates complex, data heavy workflows. Following significant growth, they're now looking for a Data Scientist to help embed intelligent capabilities directly into their core product. This is a hands-on, product-focused role where you'll design, build, and deploy AI solutions that deliver real-world impact, not just experimentation. You'll work closely with engineering and leadership to shape how AI drives the next phase of the platform.
Why join?
- Work on production AI systems with real customer impact
- High-growth environment with strong momentum
- Close collaboration with senior leadership and engineering
- Real ownership across the full model lifecycle
What you'll be doing:
- Design, build, and deploy AI/ML models powering core product features
- Work across use cases such as document processing, anomaly detection, and intelligent automation
- Own the end-to-end model lifecycle from problem definition to production and iteration
- Collaborate closely with engineers to integrate models into live systems
- Help shape the AI roadmap, identifying high-impact opportunities
- Continuously evaluate and apply relevant advancements in AI/ML
What you'll bring:
- Proven experience building and deploying AI/ML models in production
- Strong Python skills and experience with modern ML frameworks (e.g. PyTorch, TensorFlow)
- Hands-on experience with LLMs, prompt engineering, RAG, or similar approaches
- Ability to operate with high autonomy and take ownership of solutions
- Strong communication skills with both technical and non-technical stakeholders
- Commercial mindset focused on delivering real product value
Interested? If you enjoy building production-ready AI solutions and want to see your work directly influence a product, get in touch with Justin Donaldson for a confidential chat.
Data Scientist - AI employer: Ocho
Join a dynamic technology company in Belfast that is at the forefront of AI innovation, where you'll have the opportunity to work on impactful production systems and collaborate closely with senior leadership. With a strong focus on employee growth and a high-energy work culture, this role offers real ownership over the AI model lifecycle, allowing you to see the tangible results of your contributions. Embrace the chance to shape the future of intelligent automation in a supportive environment that values creativity and initiative.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist - AI
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI/ML projects. Whether it's GitHub repos or a personal website, having tangible examples of your work can really set you apart from the crowd.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical skills and be ready to discuss your experience with Python and ML frameworks. Practice common interview questions and think about how your past projects align with the role.
✨Tip Number 4
Apply through our website! We love seeing applications directly from candidates who are excited about joining us. Tailor your application to highlight your relevant experience and show how you can contribute to our mission.
We think you need these skills to ace Data Scientist - AI
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with AI/ML models and Python skills. We want to see how your background aligns with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Tell us why you’re excited about this role and how you can contribute to our mission. Be specific about your experience with production AI systems and collaboration with engineering teams.
Showcase Your Projects:If you've worked on any cool AI projects, make sure to mention them! We love seeing real-world applications of your skills, especially if they had a tangible impact. Include links or descriptions that highlight your contributions.
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 Ocho
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI and ML frameworks like PyTorch and TensorFlow. Be ready to discuss your hands-on experience with LLMs and prompt engineering, as these are key to the role.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific projects where you've designed, built, and deployed AI/ML models. Highlight how you tackled challenges and delivered real-world impact, as this will resonate with their focus on practical solutions.
✨Communicate Like a Pro
Since you'll be working with both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. This will demonstrate your strong communication skills and ability to collaborate effectively.
✨Be Ready to Take Ownership
The company values autonomy, so come prepared with examples of how you've taken ownership of projects in the past. Discuss how you managed the end-to-end model lifecycle and contributed to shaping the AI roadmap.
