Production ML Scientist: Time-Series & Anomaly Detection

We’re looking for an experienced Data Scientist to join a high-impact analytics program focused on production optimisation and large-scale anomaly detection. This role sits at the intersection of advanced analytics, engineering, and operations, delivering models that move from concept to production. Our client is expanding its use of advanced analytics and machine learning to improve and optimise production performance across the company. This role sits at the heart of a program focused on turning operational data into actionable insights that help increase reliability, reduce deferment, and uncover new optimisation opportunities. You will help design and deploy analytics that support better decision making, earlier issue detection, and more efficient operations. The work spans time-series modelling, anomaly detection, optimisation modelling, and data quality improvement, with the broader goal of driving measurable production uplift and operational efficiency improvements across the fleet. Responsibilities: Develop and operationalise machine learning models for large-scale anomaly detection and production optimisation Apply advanced time-series analysis, scalable compute frameworks, and continuous model monitoring Translate business problems into analytical hypotheses with measurable value Build high-quality, maintainable Python code aligned with enterprise standards Integrate models into production and manage the full model lifecycle, including performance and drift Work in Agile delivery teams with frequent iteration and CI/CD Communicate insights clearly to both technical and non-technical stakeholders Degree in Statistics, Mathematics, Data Science, Computer Science, or similar Proven experience delivering ML solutions into production Strong background in time-series analytics, optimisation, classification, and anomaly detection Hands-on experience with large-scale data wrangling, feature engineering, and pattern recognition Strong Python skills with modern ML and statistical libraries Solid SQL experience: exposure to Spark, Databricks, and Azure highly regarded Excellent communication skills and ability to work in cross-functional teams Pay range and compensation package: Contract: 12 months + extensions Start: ASAP Rate: Market If you’re passionate about building analytics that operate at scale and deliver real operational impact, we’d love to hear from you.

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