Location: Hybrid (strong preference for Reading office)
Hours: Monday to Friday, 37.5 hours per week
About BCNAt BCN we unite people and technology to enable organisations to fly. We believe people and organisations can achieve anything using technology to its full potential. Our role is to help them understand what is possible, implement in the right way and utilise their technology to achieve their ambitions. Which is why we put people front and centre – building client relationships for life and fostering a culture where our people thrive.
We are a leading managed IT services provider and technology consultant, specialising in delivering transformative technology solutions with industry‑leading client experience across business, public sector and not for profit organisations. From cloud computing, cybersecurity, and data management to power app development, we are dedicated to pioneering technology with Microsoft innovation.
Guided by our 3 values of building relationships, customer success and passion and dedication, we are on a mission to make BCN the most trusted tech partner in the UK today. The kind of company clients want to work with, and people want to work for.
Focus of the roleWe are looking for a DP‑100–certified Azure Data Scientist who is passionate about applied machine learning and delivering real improvements to our clients in smart, effective ways. The successful candidate will be eager to deepen their skills and broaden into wider Azure analytics capabilities, building a long career here at BCN Group within a growing and exciting innovation technology team.
Our people have three things in common: a curiosity for learning, a drive to deliver projects brilliantly, and a belief that together we make a difference.
Key Responsibilities- Work directly with business stakeholders to conceive, design and deliver end‑to‑end machine learning solutions, aligned to operational goals and governance standards.
- Prepare and transform data for modelling using Python and Azure‑native tools, ensuring quality and consistency across the ML and AI life cycles.
- Evaluate, and deploy models using AutoML, MLflow, and custom pipelines, with a focus on performance, scalability, and maintainability.
- Monitor model performance, detect drift, and implement retraining strategies to maintain relevance and accuracy.
- Apply responsible AI principles including fairness, explainability, and privacy to support ethical and transparent model development.
- Collaborate with cross‑functional teams to integrate ML and AI solutions into business processes, improving engagement, productivity, and decision‑making.
- Support our clients maintain and optimise Azure ML environments to deliver reproducible experimentation and efficient deployment.
Skills & Qualifications
- Certified in DP‑100 Azure Data Scientist Associate (mandatory).
- Confident working independently or collaboratively to support solution design, delivery, and governance across the ML and AI lifecycle.
- Experienced in designing, training, registering, and deploying models using Azure Machine Learning (AML), AutoML, and MLflow.
- Proficient in Python, pandas, and scikit‑learn for data science and feature engineering, with a strong focus on rigorous validation and experiment tracking.
- Skilled in deploying models to real‑time REST endpoints and orchestrating batch inference pipelines.
- Capable of implementing MLOps practices including CI/CD pipelines, model registry, environment management, and promotion across dev/test/prod stages.
- Solid understanding of cloud and data engineering principles including storage, compute, and pipeline orchestration.
- Strong ability to collaborate with subject matter experts to map current‑state business processes and translate them into machine learning opportunities with measurable operational impact.
- Clear communicator with excellent problem‑solving skills, able to engage effectively with both technical and non‑technical stakeholders.
- Exposure to Kubernetes, Azure AI Search, or Azure AI Foundry to support scalable and efficient solution delivery.
- Understanding of generative AI techniques and language model optimisation to enhance solution capability…
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