How your CV stacks up
Upload your CV to see how well it fits this job role
?%
This role requires relocation to Riyadh
About the Client
Our client is building an AI-first operating system for a critical, real-world industry, connecting multiple stakeholders into a single intelligent platform.
The business is already operating at scale, with thousands of active users and live enterprise deployments across multiple markets, integrating transactional, operational, and inventory data into one ecosystem.
They are now entering the next phase of growth:
👉 Evolving from predictive analytics into agentic AI systems that can autonomously make and execute decisions.
The Opportunity
This is a senior, hands-on AI leadership role with a clear mandate:
- Improve core machine learning systems
- Build intelligent, decision-making AI
- Drive measurable operational efficiency across the business
What You’ll Be Responsible For
- Owning and evolving the forecasting and optimisation engine
- Improving machine learning model accuracy across demand and inventory use cases
- Designing and deploying agentic AI systems that:
- Reduce manual intervention and inefficiencies
- Solve complex challenges such as low-frequency / sparse data forecasting
- Building and scaling production-grade ML systems and pipelines
- Working with large, multi-source datasets across operational systems
- Driving AI adoption across multiple business functions
- Leading a lean, high-impact data science team, while staying hands-on
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Experience Required:
- 7–12+ years in Data Science / Machine Learning (strong hands-on expertise)
- Proven experience building and improving forecasting models
- Strong experience with statistical and ML approaches (e.g., regression, tree-based models)
- Ability to choose and apply the right model to complex, real-world problems
- Experience deploying ML systems into production environments
- Strong coding skills (Python, ML frameworks, data pipelines)
- Experience leading teams while remaining deeply hands-on
Get help with your application
Your very own career expert that helps elevate your application to the next level.
🚫 Not Suited For:
- Purely strategic or consulting profiles
- Candidates without strong ML fundamentals
Nice to Have
- Experience with agentic AI systems or decision automation
- Exposure to optimisation, reinforcement learning, or advanced ML approaches
- Background in operations-heavy environments (e.g., logistics, marketplaces, etc.)
Why This Role
- Build AI systems that directly impact real-world operations
- Work with large-scale, high-quality datasets
- Own and shape the AI direction of a scaling business
- High visibility, high ownership, and direct access to leadership
- Opportunity to solve complex, non-trivial ML challenges
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location