We are seeking a highly analytical and technically strong Senior Data Scientist to join a growing data and analytics function. This role will focus on developing production-ready machine learning models, uncovering complex patterns in large datasets, and translating insights into real business impact.You will work closely with business stakeholders and subject‑matter experts to design analytical solutions, build AI‑driven tools, and support both operational and strategic decision‑making.Key ResponsibilitiesAnalyse, review, and interpret complex datasets through the development of models and data‑driven case studies.Develop, deploy, and maintain production‑grade machine learning and deep learning models.Identify and explain key drivers of patterns and behaviours within data to support business insights.Contribute to the design and delivery of analytics‑based tools and assets, including detection and monitoring of non‑standard patterns.Collaborate closely with subject‑matter experts and business stakeholders to explore challenges and design effective solutions.Present analytical findings clearly for both operational teams and senior business stakeholders.Support short‑ and long‑term operational and strategic initiatives using data‑driven insights.Conduct research, analysis, and implement recommended business solutions where appropriate.Required Qualifications & ExperienceMaster’s degree (or higher) in Statistics, Mathematics, Physics, Engineering, Computer Science, or a related highly quantitative discipline.Strong proficiency in machine learning, deep learning, and AI frameworks, including PyTorch.Proven hands‑on experience building and deploying machine learning models into production environments.Strong understanding of model evaluation, optimisation, and performance monitoring.Excellent analytical and problem‑solving skills.Ability to clearly communicate complex technical concepts to non‑technical stakeholders.Desirable / Nice to HaveExperience working with real‑world, large‑scale datasets.Background in developing monitoring, detection, or anomaly‑based models.Strong programming skills in Python.Exposure to cloud‑based ML platforms (AWS, Azure, or GCP).Familiarity with MLOps, CI/CD, and model lifecycle management.
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