Applied Scientist

Desired experience and qualifications

Work experience: 8+ years in applied data science, statistics, ML or operations research, with evidence of models deployed beyond prototype stage.

Expertise (e.g. professional, technical): Python and SQL; statistics/probability; design of experiments; supervised/unsupervised learning; machine learning and deep learning; time-series/forecasting; model evaluation and explainability. Optimization/operations research, reliability analytics or causal methods advantageous. Experience with process automation/RPA platforms and integration patterns (e.g., Microsoft Power Automate, Selenium or equivalent) is advantageous, particularly where automation is combined with analytical decisioning.

Engineering capability: Git, testing, APIs, containers and practical MLOps; ability to work with modern cloud/data platforms. Snowflake, Azure / Salesforce experience desirable.

Industrial experience: manufacturing, engineering, supply chain, reliability, commercial or service analytics strongly advantageous.

Education: Master's degree or equivalent in statistics, mathematics, operations research, computer science, engineering, econometrics, physics or a closely related quantitative discipline.

Certifications: Cloud / ML certifications advantageous