26 to 31 of 31 Statistical Modelling Jobs in the East of England

week Role Responsibilities (Training support will be provided) Analyze large, complex datasets to identify patterns and generate actionable insights. Build high-performing predictive models, statistical analyses, and ML pipelines across varied data types. Design and implement rigorous experiment frameworks and validation strategies. Automate workflows, feature pipelines, and reproducible research … driven research. Proficiency in Python and key libraries such as Pandas, NumPy, Polars, and scikit-learn. Solid knowledge of experiment design, causal inference, and statistical modeling. Familiarity with SQL, distributed data systems, and experiment tracking tools. Excellent communication and data storytelling skills. Application Process (Takes 20 min) Upload resume ...

week Role Responsibilities (Training support will be provided) Analyze large, complex datasets to identify patterns and generate actionable insights. Build high-performing predictive models, statistical analyses, and ML pipelines across varied data types. Design and implement rigorous experiment frameworks and validation strategies. Automate workflows, feature pipelines, and reproducible research … driven research. Proficiency in Python and key libraries such as Pandas, NumPy, Polars, and scikit-learn. Solid knowledge of experiment design, causal inference, and statistical modeling. Familiarity with SQL, distributed data systems, and experiment tracking tools. Excellent communication and data storytelling skills. Application Process (Takes 20 min) Upload resume ...

week Role Responsibilities (Training support will be provided) Analyze large, complex datasets to identify patterns and generate actionable insights. Build high-performing predictive models, statistical analyses, and ML pipelines across varied data types. Design and implement rigorous experiment frameworks and validation strategies. Automate workflows, feature pipelines, and reproducible research … driven research. Proficiency in Python and key libraries such as Pandas, NumPy, Polars, and scikit-learn. Solid knowledge of experiment design, causal inference, and statistical modeling. Familiarity with SQL, distributed data systems, and experiment tracking tools. Excellent communication and data storytelling skills. Application Process (Takes 20 min) Upload resume ...

week Role Responsibilities (Training support will be provided) Analyze large, complex datasets to identify patterns and generate actionable insights. Build high-performing predictive models, statistical analyses, and ML pipelines across varied data types. Design and implement rigorous experiment frameworks and validation strategies. Automate workflows, feature pipelines, and reproducible research … driven research. Proficiency in Python and key libraries such as Pandas, NumPy, Polars, and scikit-learn. Solid knowledge of experiment design, causal inference, and statistical modeling. Familiarity with SQL, distributed data systems, and experiment tracking tools. Excellent communication and data storytelling skills. Application Process (Takes 20 min) Upload resume ...

cyclic spectra, EVM, autocorrelation, constellation tracking, etc.) Designing RF data-processing pipelines built around practical hardware constraints (bandwidth, ADC limits, gain stages, timing jitter) Modelling RF front-end behaviour (filters, mixers, LOs, AGC, noise figure) to improve signal integrity and inference accuracy Developing ML and statistical models … Python proficiency for RF data analysis and prototyping (NumPy, SciPy, matplotlib, scikit-learn, PyTorch) Solid understanding of DSP fundamentals (FFT, filtering, modulation, correlation, noise modelling, resampling) Familiarity with SDR frameworks such as GNU Radio, SDRangel, osmoSDR, or SoapySDR Practical understanding of RF hardware chains (antenna filters mixers ...

cyclic spectra, EVM, autocorrelation, constellation tracking, etc.) Designing RF data-processing pipelines built around practical hardware constraints (bandwidth, ADC limits, gain stages, timing jitter) Modelling RF front-end behaviour (filters, mixers, LOs, AGC, noise figure) to improve signal integrity and inference accuracy Developing ML and statistical models … Python proficiency for RF data analysis and prototyping (NumPy, SciPy, matplotlib, scikit-learn, PyTorch) Solid understanding of DSP fundamentals (FFT, filtering, modulation, correlation, noise modelling, resampling) Familiarity with SDR frameworks such as GNU Radio, SDRangel, osmoSDR, or SoapySDR Practical understanding of RF hardware chains (antenna ? filters ? mixers ...