24 of 24 Remote/Hybrid Bayesian Methods Jobs in the UK

deployment in laboratories, hospitals, and public health organisations worldwide. Your Role: As a (Senior) Scientist, you will design, develop, and evaluate novel computational methods for translating metagenomic sequencing data into actionable results in a clinical or public health context. You will develop algorithms and AI/ML methods … Develop ML/AI techniques to address real-world problems in the pathogen genomics space, in collaboration with scientists across EIT Validate and benchmark methods using public and internal datasetsWork with bioinformaticians and software engineers to implement methods in scalable, reproducible, and modular workflows Communicate technical work clearly ...

both technical and non-technical audiences. A proven track record of turning business problems into measurable outcomes. Nice to Have Experience with Bayesian modelling, optimisation algorithms or multi-armed bandits. Exposure to Generative AI, LLMs or agentic AI systems. MLOps experience, including CI/CD, model monitoring ...

stakeholders Hands-on experience with a range of models, such as time-series forecasting, gradient boosting, clustering, NLP and Bayesian methods Strong MLOps: orchestration, experiment tracking, hyperparameter tuning and automated retraining pipelines Object-oriented Python, Polars or PySpark, and data versioning (e.g. DVC), plus experience designing ...

pricing models.* Turning pricing opportunities into measurable hypotheses, experiments and production changes.* Evaluating pricing performance through backtesting, online testing and commercial metrics.* Developing Bayesian, multi-armed bandit and other optimisation approaches for dynamic pricing.* Working with commercial, finance and product teams to understand pricing performance and recommend … code, testing and code review, alongside strong SQL.* A solid grounding in machine learning techniques such as gradient boosting, GLMs, Bayesian methods and multi-armed bandits, or comparable experimentation and optimisation methods.* Experience designing, running and evaluating pricing experiments using both commercial and statistical measures. ...

international clients, from data strategy and collection to modelling, insights, and activation. Apply econometrics, regression, Bayesian statistics, and machine learning methods to analyse marketing and customer data. Collaborate closely with Managers to understand the project scope, structure, analytical approaches, manage operations and ensure timely delivery. Build … similar tools. Experience with Databricks, Azure, or other cloud/data platforms is a plus. Solid understanding of econometrics, regression analysis, Bayesian statistics, or other advanced modelling techniques. Experience translating data and model outputs into actionable business recommendations. Comfortable handling large datasets, optimizing data pipelines, and delivering ...

attribution and customer acquisition economics. Commercially minded, with the ability to influence marketing strategy. An AI-first approach to data science. Experience with Bayesian modelling, value-based bidding or LTV modelling would be advantageous. Package: £70,000-£90,000 + bonus and benefits Location: Fully remote within ...

world physical systems. Must-Have Requirements Strong Python experience, particularly for data pipelines. Experience with probabilistic time-series forecasting , including Bayesian methods, PyMC, Amazon DeepAR or similar. Experience working with small or scarce datasets for distribution prediction. Proven ability to build data pipelines/database architectures ...

algorithms, tuning, and performance evaluation. Experience with a range of feature engineering techniques (e.g., target encoding). Solid grasp of frequentist and Bayesian statistics for parameter estimation and experimentation. Experience in writing clean, production‐grade Python code for both model training and inference. Excited to leverage LLMs ...

algorithms, tuning, and performance evaluation. Experience with a range of feature engineering techniques (e.g. target encoding). Solid grasp of frequentist and Bayesian statistics for parameter estimation and experimentation. Experience in writing clean, production-grade Python code for both model training and inference. Excited to leverage LLMs ...

products PhD or other experience in a research environment Deep experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering Strong stats or math background Visualization, data skills, SQL, matplotlib, etc. Unleash Your Potential When you join Salesforce ...

products PhD or other experience in a research environment Deep experience in an applicable ML area - E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering Strong stats or math background At Fin, we want to give people what they need to do the best work ...

psychology at Oxford. You'll also work with Phil Cowans, our fractional CTO, who co‐founded Songkick and Nested as CTO and studied Bayesian machine learning at Cambridge (the maths behind probabilistic risk pricing). Why join Bite The problem is genuinely hard. A tender pack ...

initiative and are deeply accountable to your internal customers and engineering colleagues. Bonus: experience with implementing solutions for adaptive experimentation ML (contextual bandits, Bayesian optimization or RL-based allocation) Additional Information Bring all of you to work We create the conditions for high performers to thrive, through ...

initiative and are deeply accountable to your internal customers and engineering colleagues. Bonus: experience with implementing solutions for adaptive experimentation ML (contextual bandits, Bayesian optimization or RL-based allocation) Additional Information Bring all of you to work We create the conditions for high performers to thrive, through ...

delivery, and ensure actionable insights reach senior stakeholders and C-suite executives. You will build dashboards, apply econometrics and Bayesian methods, and translate complex results into practical recommendations, driving ROI and client success. Hybrid work with a central London base. #J-18808-Ljbffr ...

cycles of antibody optimisation. You will enable a data-first ecosystem by processing complex datasets and extracting key insights, with an emphasis on Bayesian modelling and ML techniques. You will work in a hybrid setting with a Bermondsey office presence and occasional collaboration with wet lab scientists ...

and validation of spectral data in high-dimensional, small-sample settings (p ≫ n, typically N < 200 per cohort). Choose and develop the right methods: chemometrics and dimensionality reduction (e. g. PLS, PCA, wavelets, regularised and Bayesian models), and, where the data support it, physics-informed … regulated product development. The opportunity Own the scientific core of a proprietary diagnostic platform, work directly with iLoF's leadership, and see your methods shape a clinical test. iLOF in a nutshell As personalized medicine becomes the norm, scientists, patients, and healthcare systems worldwide face massive barriers in providing ...

models, machine learning models, and visualisations for experiments that allow us to better understand the therapeutic potential of our antibodies. Implement and develop novel methods for a variety of applied antibody molecule engineering and drug development problems, from target ID to supporting pre-clinical operations. Work on challenging statistical … problems using Bayesian modelling; and optimisation problems using Active Learning & Bayesian Optimisation. Write high quality code to maintain and enhance our technology. Enable a data-first ecosystem at LabGenius through your proficiency at processing complex datasets and extracting key insights. What we’re looking ...

Role We are looking for a biostatistician with expertise in Bayesian modelling to work on probabilistic modelling of physiological data and medical risk. The role focuses on developing statistical frameworks that combine multiple data sources to estimate the probability of life-threatening deterioration and support triage prioritisation. … engineers, medical advisors, and the product team to design models that operate in real-world environments with noisy and incomplete data. Responsibilities Develop Bayesian statistical models to estimate physiological deterioration risk from multi-sensor data Build probabilistic frameworks integrating vital signs, haemodynamic indicators, motion data, and environmental ...

data and audiences we build for. Comfortable with sport-driven modelling decisions. Machine Learning & Statistics: Solid grounding in machine learning, supervised and unsupervised methods, and classical statistical techniques. Comfortable working with probabilistic models, uncertainty estimation and Bayesian inference. Model Development: Understanding of the full model training … Engineering: Experience building and maintaining production data pipelines, or working with AWS services such as Lambda, EventBridge and DynamoDB. Simulation: Experience with Monte Carlo methods or probabilistic simulation. AI Integration: Comfortable using AI-assisted coding tools such as Claude Code or Cursor as part of your everyday workflow, and ...

predictive models look like in a betting context and build models on your own. Support the team in maintaining the codebase. Research new methods for future applications. ABOUT YOU: Required: Master’s degree or equivalent/higher qualification in one of the following disciplines: Data Science, Statistics, Mathematics, Software … closely related field. Experienced in predictive modelling, with a deep understanding of data analysis and modelling techniques such as GLMs, Time-Series Analysis, Bayesian Statistics, MCMC, neural networks, etc. Very strong skills in R or python. Advanced coding and analytical skills. Strong communication skills, fluency in English. ...

uncertainty quantification, experimental design, causal inference and Bayesian modeling. Just as essential is commercial instinct: the judgment to design rigorous, workable methods within real product goals and constraints, built through meaningful, hands-on experience shipping at startup speed. You will report to the CTO and work … product, and customer context. You need complete information before acting, rather than exercising judgment under uncertainty and evolving guidance. You'd rather follow established methods than create structure from ambiguity; defining and refining our evaluation process is core to the job. You're uncomfortable owning the quality bar and ...

data transformations using distributed computing (e.g., Spark, Dask) and ensure robust test coverage for production systems. Mentor junior team members and utilise model explainability methods to drive feature performance improvements. About You 5+ years of experience in designing, building and maintaining machine learning models to solve complex, large-scale … business problems. Deep understanding of frequentist and Bayesian statistics, plus supervised and unsupervised modelling techniques. Proven experience modelling complex interactions (e.g., cluster or network effects). Expertise in model explainability to tune feature engineering and understand feature interactions. Ability to write high-quality, production-grade Python code ...

each 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 ...