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Senior Data Scientist

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Senior Data Scientist (ML Platform & Production)
Senior individual contributor role at a scaling AI-first software business
Own the full data-to-production lifecycle across ML models, agents and platform infrastructure Belfast based, hybrid working Salary £95,000 to £110,000 UK work authorisation required
About the Company
Our client is a fast-scaling, AI-first software business building cutting-edge agent and LLM-based systems at scale. With a cross-functional engineering team that moves quickly and a genuine commitment to technical excellence, this is an environment where senior data professionals can take real ownership of complex, meaningful problems. The Belfast team sits at the heart of the company's AI engineering capability, working on challenges that are shaping the future of intelligent software.
The Role
A newly created senior individual contributor position bridging the gap between exploratory machine learning research and high-scale, reliable production systems. You will own the full data-to-production lifecycle, partnering closely with data scientists to turn complex experimental models and agentic workflows into robust, reproducible pipelines. Alongside delivery, you will establish observability standards, lead deployment practices, drive platform roadmap development and mentor engineers across the team. This role suits a senior ML or data engineering professional who is equally comfortable in the weeds of a training pipeline and setting the technical direction for a growing platform.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Key Responsibilities
- Build and maintain reliable, reproducible pipelines for training data, feature generation and embeddings, ensuring models train on accurate and well-understood data
- Partner with data scientists to make training pipelines robust, reproducible and easy to iterate on
- Own the reliability, monitoring and incident response for ML models and agents running in production, including CI/CD, versioning, canary and shadow deployment, and rollback
- Build observability into ML services covering latency, error rates, drift detection and quality regressions, with actionable alerting
- Assist with developing the one to two year roadmap for the team's data and ML platform in partnership with data platform and infrastructure leads
- Set engineering standards across the data-to-production lifecycle, conduct design reviews and mentor engineers on production-grade practices
- Work closely with infrastructure and release teams, absorbing ML serving and pipeline work currently distributed across the team
What You'll Need
Essential:
- Bachelor's degree in Computer Science, Engineering or a related field, or equivalent practical experience
- 5 or more years of experience spanning data engineering and ML production engineering, including 2 or more years specifically in MLOps or ML production systems
- Hands-on production experience with Google Cloud Platform, specifically Vertex AI and BigQuery
- Strong experience building data and feature pipelines for ML training, not just serving pipelines
- Hands-on experience with ML pipeline tooling such as MLflow, Kubeflow, Vertex AI or SageMaker, and CI/CD for model lifecycle management
- Strong experience with cloud infrastructure and container and orchestration tooling including Docker and Kubernetes
- Proven track record owning production incidents for ML and data systems, including detection, mitigation, rollback and post-incident follow-through
- Strong software engineering fundamentals in Python, Go or Java
- Experience mentoring engineers and influencing technical direction without direct authority


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Desirable:
- Direct experience partnering with data scientists on feature engineering or model training pipelines
- Experience operating LLM or agent-based systems in production including LLMOps
- Master's degree in Computer Science, Engineering or a related field
- Background mentoring less experienced engineers moving into production-facing work
Why Apply?
- Salary of £95,000 to £110,000
- Newly created senior role with full ownership of ML platform strategy and production reliability at a scaling AI business
- Work at the cutting edge of MLOps, LLM deployment and agentic AI systems in production
- Close-knit, cross-functional engineering team with a strong culture of technical excellence and mentorship
- Belfast based with a business that is genuinely pushing the boundaries of intelligent software
Interested?
For a confidential conversation about this opportunity, connect with Justin Donaldson on LinkedIn or submit your CV via the link below.
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