76 to 81 of 81 Permanent Statistical Modelling Jobs

models, including Generative AI and large language models. Design and deliver synthetic data and data augmentation solutions that enhance existing data assets. Run complex statistical experiments to test model performance and validate hypotheses. Work closely with Product and Engineering to move models from prototype into scalable, production-ready solutions. … text generation or data synthesis. Advanced Python skills within a data science and machine learning stack, alongside strong SQL capability. Solid grounding in statistical methods, experimentation and model evaluation. Experience working with large-scale datasets and modern data platforms. Ability to explain complex technical concepts clearly to non-technical ...

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 ...

data science and analytics solutions to solve complex business problems * Building internal tools and contributing to the development of data and AI products * Conducting statistical analysis and regression modelling to generate insights * Creating dashboards and visual outputs for business stakeholders * Supporting AI workflow development, including exposure to large … Proficiency in Python, including libraries such as Pandas, NumPy and scikit learn * Strong SQL skills and experience working with structured data * Solid understanding of statistical analysis and regression techniques * Exposure to cloud platforms, ideally Azure, and an understanding of deployment processes * Experience working in cross functional teams, ideally alongside ...

actuarial pricing solutions within insurance Strong understanding of insurance products and pricing methodologies across relevant lines Solid knowledge of actuarial methods, rating concepts, statistical techniques, modelling and pricing governance Experience working with clients on transformation or implementation programmes Ability to operate in cross-functional agile teams and work ...

strategies. Testing, validating, and debugging non-deterministic AI systems. Advising stakeholders on the risks, limitations, and appropriate use cases for AI technologies. Determining when statistical models, traditional machine learning approaches, or deterministic logic are more suitable than generative AI. Driving engineering best practice across AI development, deployment, governance … experience with demonstrated technical leadership. Experience integrating AI capabilities into production applications and business workflows. Strong understanding of LLM architectures, machine learning models, and statistical methods. Practical experience building and deploying RAG solutions. Experience evaluating AI systems and improving reliability, safety, and performance. Strong software engineering, architecture, and systems ...

Rate: £402 per day all inc. (PAYE through Umbrella) Role Description: SAS Model Development & Enhancement (SAS Model Developer) 1. Design, develop, and implement statistical, pricing, or predictive models using SAS. 2. Build modelling datasets, feature engineering pipelines, and variable transformations. 3. Implement model logic, segmentation rules, scoring code … experience in: 1. SAS Base, SAS Macros, Data Step programming 2. SAS SQL 3. SAS Enterprise Guide or SAS Studio Strong understanding of modelling concepts such as: 1. Regression (linear/logistic) 2. Time-series forecasting 3. Segmentation models 4. Risk, pricing, or predictive modelling Experience with model ...