Senior Data Scientist

Ocho; Belfast City District; Hybrid; GBP 90,000 - 140,000; Full time

Job summary

Ocho in Belfast, UK is seeking a Senior Data Scientist to own the full data-to-production lifecycle for ML models, agents, and platform infrastructure. You will partner with the Head of Data Science to harden production models, build reliable pipelines and drive MLOps end-to-end.

The role blends research and production, requiring hands-on work with GCP Vertex AI/BigQuery, Docker/Kubernetes, and CI/CD, while influencing platform roadmap and deployment practices on a globally distributed team.

Qualifications

• Advanced degree in a relevant STEM field.
• 5+ years across data engineering and ML production engineering, incl. 2+ years in MLOps
• Proven track record deploying and maintaining live, customer-facing ML systems at scale
• Hands-on production experience with cloud platforms (GCP Vertex AI/BigQuery, AWS or Azure)
• Experience with ML pipeline tooling (MLflow, Kubeflow, Vertex AI) and CI/CD for model lifecycle
• Experience with Docker, Kubernetes and cloud infrastructure
• Experience operating LLM or agent-based systems in production (LLMOps)
• Direct experience partnering with data scientists on feature engineering or model training
• Strong Python, Go or Java fundamentals

Responsibilities

• Scale and harden ML models from R&D into production, with observability.
• Build reproducible pipelines for data, features and embeddings.
• Own ML model reliability, monitoring, CI/CD, versioning, canary deployment and rollback.
• Establish observability standards and deployment practices for the platform.
• Contribute to the 1–2 year roadmap for data and ML platform.
• Mentor engineers on production-grade practices and review designs.
• Collaborate with globally distributed, async-first teams across infra and release.

Skills

Python

Go

Java

Feature engineering

LLMOps

Production ML systems

Education

Master's or PhD in a relevant STEM field

Tools

Vertex AI

BigQuery

Docker

Kubernetes

MLflow

Kubeflow

CI/CD for ML

AWS

Azure

Job description

Senior Data Scientist (ML Platform & Production)

• Senior individual contributor role at a fast-scaling, AI-first software business
• Own the full data-to-production lifecycle across ML models, agents and platform infrastructure
• Belfast based, hybrid with async-friendly global team
• Salary: competitive, reflecting experience, with equity
• UK work authorisation required

About the Company

Our client is a fast-scaling AI software business powering enterprise automation for Fortune 500 clients including major names across financial services and healthcare technology. Their small, elite Data Science and AI team builds and deploys cutting-edge ML and agentic AI systems at scale, with a culture built around intellectual curiosity, hands‑on leadership and pragmatic startup thinking. Leaders stay close to the code, debate ideas openly and move fast without corporate inertia. This is a team where exceptional engineers thrive.

The Role

A newly created senior role bridging the gap between machine learning research and high-scale production systems. You will partner closely with the Head of Data Science to harden existing production models, build reliable data and feature pipelines, and own the full MLOps lifecycle from deployment through to monitoring, incident response and continuous improvement. Alongside delivery, you will establish observability standards, lead deployment practices and contribute to platform roadmap development. This role suits someone equally comfortable in the weeds of a training pipeline and setting technical direction for a growing platform.

Key Responsibilities

• Scale and harden existing deep learning models from R&D into reliable, observable production systems
• Build and maintain reproducible pipelines for training data, feature generation and embeddings
• Own reliability, monitoring and incident response for ML models and agents in production, including CI/CD, versioning, canary deployment and rollback
• Build observability into ML services covering latency, error rates, drift detection and quality regressions
• Contribute to the one to two year roadmap for the data and ML platform
• Set engineering standards, conduct design reviews and mentor engineers on production‑grade practices
• Work closely with infrastructure and release teams across a globally distributed, async-first team

What You'll Need

• Strong academic foundation in Applied Mathematics, Physics, Astrophysics or a hard STEM discipline
• 5 or more years across data engineering and ML production engineering, including 2 or more years in MLOps or ML production systems
• Proven track record deploying and maintaining live, customer‑facing ML systems at scale in production environments
• Hands‑on production experience with Google Cloud Platform, specifically Vertex AI and BigQuery, or equivalent AWS or Azure experience
• Strong experience building data and feature pipelines for ML training
• Experience with ML pipeline tooling such as MLflow, Kubeflow or Vertex AI, and CI/CD for model lifecycle management
• Experience with Docker, Kubernetes and cloud infrastructure
• Proven track record owning production incidents including detection, mitigation and rollback
• Strong Python, Go or Java fundamentals
• Experience mentoring engineers and influencing technical direction
• Experience operating LLM or agent‑based systems in production including LLMOps
• Direct experience partnering with data scientists on feature engineering or model training
• Master's or PhD in a relevant STEM field

Why Apply?

• Competitive salary plus equity, with package tailored to UK, NI or European candidates
• Work directly with the Head of Data Science on mission‑critical production systems for Fortune 500 clients
• Hands‑on, intellectually driven team that debates ideas openly and challenges assumptions constructively
• Async‑friendly culture with approximately three syncs per week, designed to protect deep focus and work‑life balance
• Fast-moving startup environment with full operational autonomy and no corporate inertia
• Belfast based with a globally distributed, elite AI engineering team behind you