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Data Scientist

Job in Sheffield, South Yorkshire, S5, England, UK
Listing for: RED Global
Full Time position
Listed on 2026-09-13
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Scientist
Salary/Wage Range or Industry Benchmark: 60000 - 90000 GBP Yearly GBP 60000.00 90000.00 YEAR
Job Description & How to Apply Below

We are looking for an experienced Data Scientist with strong Machine Learning, Google Cloud Platform (GCP), Python and data engineering expertise to support the optimisation of fraud models and ML infrastructure.

Contract information

Job title:

Data Scientist

Location:

3 days in Sheffield and 2 days remote

Contract type:
Inside IR35

Key Responsibilities
  • Assess and optimise existing fraud and machine learning models, identifying opportunities to improve performance and reduce compute and inference costs.
  • Produce practical, implementation-ready recommendations, including estimated effort, cost savings and technical impact.
  • Provide both configuration-level and code-level guidance to engineering and data science teams.
  • Analyse and optimise GCP compute, storage and networking, balancing cost, performance and reliability.
  • Implement and improve monitoring and observability across ML workloads, including cost, performance and reliability metrics.
  • Support the design, validation and deployment of fraud and machine learning models end-to-end.
  • Strong commercial experience as a Data Scientist, ML Engineer or similarly technical Machine Learning specialist.
  • Strong hands-on experience with Google Cloud Platform (GCP).
  • Experience optimising cloud-based workloads for cost, performance and reliability.
  • Strong SQL.
  • Experience building, supporting or optimising production Machine Learning models.
  • Experience with end-to-end ML and data pipelines.
  • Strong understanding of model training, inference and feature engineering.
  • Experience with Spark or similar distributed data processing technologies.
  • Experience implementing engineering best practices including CI/CD and automated testing.
  • Ability to analyse an existing technical environment and provide clear, actionable and commercially measurable recommendations.
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