13 of 13 Permanent Statistical Inference Jobs in the UK

shaping the future of marketing technology — and actually enjoys doing it — you're in the right place. Find us on Instagram: @optimizely Introduction Rigorous statistical analysis is a core to all experimentation products at Optimizely. You will get on customer calls to articulate how we maintain statistical accuracy … products as well as triage questions around statistical inference. You will educate internal and external stakeholders about fundamental as well as cutting edge statistics concepts via webinars, speaking engagements, blog posts, and white papers. You will also have the opportunity to work with our product and engineering teams ...

makes use of the evidence conventionaldata systems miss – from large internal text datasets to signals spread across many external sources. Our architecture combines comparative statisticalinference and causal frameworks with machine learning and large languagemodels, ensuring stable interpretation andconsistent quality at scale. We’re backed by a specialist AI venture fund … hiring an Applied Scientist to invent, validate and implement methods forworking out what drives outcomes from unstructured evidence. You’ll explore thefrontier between statistical and causal inference and large language models – designingexperiments, prototyping pipelines, and collaborating with engineers tobring your best ideas into production quickly. You’ll work ...

Highly proficient in writing optimized, complex queries across large cloud data warehouses (e.g., Snowflake, BigQuery). Programming & Modelling: Strong proficiency in Python for statistical modeling, forecasting, and machine learning. Statistics & Math: Deep understanding of statistical inference, regression analysis, probability theory, decision trees, and hypothesis testing (p-values … quantitative analytics or data science role in a fast‐paced environment. Business Acumen: Demonstrated track record of framing business problems into mathematical/statistical frameworks and outputting actionable recommendations. Communication: Ability to distill complex statistical concepts into clear, plain language for non‐technical executives. Nice‐to‐Haves: Experience ...

client’s team in Central London. You’ll play a pivotal role in driving data-informed decision-making through advanced A/B testing, statistical analysis, and enterprise-level business intelligence solutions This is a client-facing position where you’ll work embedded within the client’s team, requiring … initiative, and the ability to represent CI&T professionally Design, implement, and analyze A/B tests to measure product and feature performance Apply statistical methods to ensure test validity and generate actionable insights Present findings and recommendations to stakeholders Design, build, and optimize semantic data models in Power ...

professional expertise in data science, computer science, statistics, mathematics, artificial intelligence, machine learning or another relevant quantitative discipline. Strong practical experience applying data science, statistical modelling and machine learning to complex real-world problems. Advanced proficiency in Python and/or R, SQL and modern data-analysis and machine … professional expertise in data science, computer science, statistics, mathematics, artificial intelligence, machine learning or another relevant quantitative discipline. Strong practical experience applying data science, statistical modelling and machine learning to complex real-world problems. Advanced proficiency in Python and/or R, SQL and modern data-analysis and machine ...

engagement, and operational efficiency, helping the business make informed decisions through robust analysis, experimentation, and modelling. How you'll contribute: Build and iterate on statistical and machine learning models to solve business problems across areas such as credit risk, fraud, customer engagement, and operational efficiency. Partner with stakeholders … pipelines and model documentation. Monitor models in production, identify performance drift, propose improvements, and support ongoing recalibration or retraining where required. Apply probability and statistical inference to design experiments, interpret results, and provide clear recommendations to stakeholders. Contribute to high quality data practices by identifying data quality issues ...

iPlayer, Sounds, News and Sport—reach millions of people every week and generate billions of audience interactions. As a Data Scientist, you will develop statistical and machine learning models that help understand audience behaviour, improve audience measurement, and support strategic decision-making across the BBC. Working with a range … dedicated time to develop your technical skills, explore new approaches and contribute to best practice across the organisation. YOUR KEY RESPONSIBILITIES AND IMPACT Apply statistical and machine learning techniques to answer business questions and improve understanding of audience behaviour, combining data from multiple sources including digital activity data, audience ...

join our Research and Intelligence organisation in London. You'll work across flexible, cross-functional squads within the Data Science team, leading analytical, statistical, and machine-learning work across both UTXO and EVM blockchains. The team develops behavioural heuristics, graph algorithms, statistical models, and machine-learning techniques that … projects or systems, translating broad problem statements into actionable work, managing evolving requirements, and delivering measurable outcomes. Design, develop, and validate novel analytical methods, statistical models, behavioural heuristics, and algorithms across UTXO, EVM, and other blockchain data to attribute on-chain activity and uncover customer-relevant insights. Stay current ...

Data Scientist Organisation BBC Organisation BBC Locations Salford, UK Application Deadline 2 days remaining Apply statistical and machine learning techniques to answer business questions and improve understanding of audience behaviour, combining data from multiple sources including digital activity data, audience panels and surveys. Contribute to the design, development … mathematics, statistics, computer science, econometrics or related field, or equivalent work experience. Strong analytical and problem-solving skills, with experience applying data science and statistical techniques to solve business problems by translating ambiguous business questions into practical analytical solutions and selecting appropriate methods, models or algorithms. Understanding of statistical ...

stage of the consumer’s lifecycle. Experience overseeing experimentation programmes and practices that inform product or business decisions. A good understanding of methods for statistical inference (e.g. Bayesian, Frequentist) and familiarity with predictive analytics techniques is highly beneficial. Working knowledge of common analytics tools used for tracking ...

heuristics and algorithms over EVM (and other) blockchain data to attribute on‐chain activity and uncover new insights. Apply advanced techniques including graph computation, statistical modeling, and machine learning to large‐scale on‐chain datasets. Identify and resolve inefficiencies in code, methodology, and workflows; ensure your work integrates cleanly … Python and SQL, with a track record of writing clean, testable, production‐quality code. Demonstrated experience applying advanced analytical techniques (e.g. graph algorithms, ML, statistical inference) to large, messy datasets. Comfort working with EVM‐based blockchain data, or strong evidence of the aptitude to ramp up quickly ...

Engineering. 3–5 years as a quantitative analyst/programmer in asset management or investment banking. Strong grounding in probability theory, stochastic calculus and statistical inference. Experience across liquid and illiquid assets, asset allocation and portfolio optimisation. Practical exposure to bond pricing, stochastic volatility modelling and Monte Carlo simulations. ...

opportunity for a Machine Learning Engineer with a strong quantitative background to work on real‐world prediction problems within financial markets. The role combines statistical modelling, machine learning research, natural language processing, and large language model applications in a production investment environment. You will develop predictive models across fixed … issuer credit deterioration, transaction costs, liquidity forecasting, and relative‐value opportunities. Apply machine learning techniques to low signal‐to‐noise datasets where robustness and statistical discipline are critical. Conduct extensive out‐of‐sample testing and validation to ensure model reliability and performance. Evaluate model effectiveness using appropriate statistical ...