4 of 4 Permanent Statistical Modelling Jobs in Berkshire

security, and scaling Hands-on experience with Docker and Kubernetes in real-world engineering workflows Solid grasp of ML fundamentals: supervised/unsupervised learning, statistical modelling, evaluation A pragmatic approach to engineering capable of balancing speed, risk, and delivery in complex environments Excellent communication and collaboration skills, especially ...

drive to build production-grade solutions that scale. The Senior Python Software Engineer – Analytics & Optimisation will: – Design and maintain well-structured Python modules for modelling and forecasting – Build optimisation algorithms to solve real-world marketing challenges – Implement scalable data pipelines using cloud-native tools – Champion high coding standards with … 5+ years' experience with Python and scientific libraries (especially SciPy) – A Master's in Maths, Computer Science, or similar quantitative field – Strong grasp of statistical modelling and numerical optimisation – Experience with scalable data/analytics architecture in a product setting – Familiarity with CI/CD, Docker, Kubernetes ...

focused environment. Proficiency in SQL and Python or R, with experience using BI tools such as Power BI, Tableau, or Looker Studio. Confident with statistical analysis, predictive modelling, and translating insights into clear recommendations. Comfortable working in a fast-paced setting where collaboration and initiative are key. Interview ...

succeed Not the classic \"predictive modeling\" skillset Data Science skillset Needed skills: Exploration vs. exploitation mindset Advanced Optimization Skills: Expertise in linear optimization and statistical optimization for systems. Strong background in modeling and solving problems involving variability and constraints. Ability to search optimal recipe space within a model. Build … predict outcomes. Operations research: handling constraints, finding optimal arrangements for fastest packing. Stochastic simulation: accounting for variability in machine speeds and conveyor setups. Techniques: statistical simulation, stochastic modeling, linear optimization. Industry Experience: Exposure to renewable energy, manufacturing, electronic systems or distribution (Retail/Food). Tools & Platforms: Databricks ...