Principal Data Scientist

Principal Data Scientist

Permanent, Full-Time

Westhill, Aberdeen with Hybrid working

This senior role is embedded within a pioneering Digital Innovation team at the heart of the Energy Division’s strategy. You will lead transformative data science initiatives that drive operational efficiency and sustainability. From offshore wind farms to subsea engineering and large-scale energy infrastructure, you’ll design and deliver enterprise-grade data products and deploy advanced machine learning models into production environments.

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• Lead end-to-end data science projects, from requirements gathering to production deployment, ensuring best practices and alignment with the Head of Digital.
  
• Translate complex business challenges into data-driven solutions that deliver efficiency gains, risk reduction, and customer value.
  
• Design, build, and deploy advanced ML/AI models (e.g., supervised/unsupervised learning, deep learning, time-series analysis) into scalable production environments.
  
• Establish robust data quality frameworks for high-volume sensor and operational datasets, ensuring reliability and integrity.
  
• Drive innovation through R&D, prototyping, and validation of new data science approaches to create competitive advantage.
  
• Collaborate with senior stakeholders across product, engineering, and business functions, aligning initiatives with strategic objectives and regulatory requirements.
  
• Mentor and develop data science talent, fostering a high-performance, collaborative culture and championing best practices in MLOps and reproducible research.
  
• Communicate insights and technical concepts clearly to technical and non-technical audiences, influencing enterprise data strategy and AI adoption roadmaps.
  

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• Strong expertise in Python and core data science libraries (NumPy, Pandas, Scikit‑Learn, PyTorch, TensorFlow).
  
• Deep knowledge of machine learning and AI techniques, including supervised/unsupervised learning, deep learning, time‑series modelling, and LLMs (fine‑tuning and RAG).
  
• Experience implementing data quality and governance frameworks for large‑scale, real‑world datasets.
  
• Proficient in MLOps practices, including CI/CD, model monitoring, versioning, and reproducibility.
  
• Strong knowledge of distributed computing and real‑time data streaming technologies (Kafka, Spark, Ray).
  
• Experience with time‑series and sensor data, optimizing model precision, recall, and efficiency.
  
• Excellent communication and stakeholder management skills, with ability to translate technical concepts into business outcomes.
  
• Strong statistical modelling, problem‑solving, and leadership experience in mentoring and developing data science teams.
  

James Fisher is a global engineering services company with over 50 years of experience delivering complex offshore energy projects in some of the world’s most challenging environments. We operate across Energy, Defence, and Maritime Transport, leveraging cutting‑edge technology and deep expertise to support the full lifecycle of our customers’ assets.

In the Energy Division, we provide safe, efficient solutions across oil & gas and renewables – from well support and full‑field decommissioning to integrated services for offshore wind and expert subsea inspection, repair, and maintenance. Our work helps operators extend asset life, reduce downtime, and respond rapidly to operational challenges, driving the global shift toward a cleaner, more sustainable future.

Our One James Fisher strategy unites our capabilities under a single vision, building a stronger, more cohesive business within the Blue Economy.

Due to the volume of applications we receive for our vacancies, on occasion applications may close before the deadline, so please apply early to avoid disappointment.

James Fisher and Sons are committed to taking positive action on diversity and strongly encourage applications for candidates from all backgrounds. We are proud to be a Disability Confident employer and recognise that our success depends on our talented and diverse workforce.