1 to 25 of 27 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 ...

related to consumer behaviour, market trends, and campaign performance. Build, maintain, and apply statistical and predictive models, including regression, econometrics, Bayesian methods, and Marketing Mix Modelling (MMM). Develop dashboards, charts, and visualizations to communicate insights effectively to clients and internal teams. Assist in developing marketing ...

Nice-to-have Skills Experience in more than one of simulation, optimisation, statistical forecasting or machine learning Monte Carlo simulation, Bayesian methods or uncertainty quantification Experience building APIs or back-end services in Python (e.g. FastAPI) Experience building front ends or interfaces in JavaScript ...

fundamentals Advanced data skills: statistical modelling, machine learning, time‐series forecasting, demand prediction, optimisation, inventory management Experience with dynamic pricing, stochastic processes, or Bayesian inference is a plus Preferred Experience Background in pricing, forecasting or optimisation roles within airlines, hospitality, car rentals, e‐commerce, or similar dynamic ...

communication skills. Beneficial to have: Experience in a similar role in a professional football environment. Experience with Time-Series Analysis & Forecasting. Experience with Bayesian inference/MCMC. What's in it for you? We are committed to ensuring everyone can flourish in their roles. To achieve this ...

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 ...

and deploy production‐grade ML systems with scalability and robustness in mind. Translate state‐of‐the‐art research (probabilistic modelling, Bayesian methods, optimisation) into customer‐ready solutions. Work collaboratively within a cross‐functional team to deliver measurable impact to global shipping customers. Communicate complex ideas clearly … What We’re Looking For Familiarity and some experience with machine learning research or applied ML, ideally with expertise in probabilistic models and Bayesian statistics. Experience bringing ML models from prototype to production with supervision. Strong analytical and problem‐solving abilities, and confidence working across disciplines following ...

technical leadership: mentoring, setting standards, and influencing scientific and technical direction beyond your own projects. Beneficial Skills Practical experience with active learning, Bayesian optimisation, conformal prediction, or uncertainty quantification in iterative real‐world loops. Familiarity with retrosynthesis ML, computer‐aided synthesis planning (CASP), or reaction‐condition/ ...

what questions should be explored next. Key Responsibilities & Skills ** Develop predictive models and forecasts to identify potential future outcomes and emerging trends ** Applying Bayesian modelling, uncertainty estimation and statistical validation ** Carry out segmentation and subgroup analysis to identify meaningful differences and patterns ** Analyse longitudinal and time-series ...

Track record of promoting statistical rigour and experimental best practices in your prior roles. Prior experience using causal inference/econometric techniques and bayesian methodologies for hypothesis testing. Prior experience using large datasets with distributed computing (e.g. spark, hadoop or other map-reduce tech) Experience working ...

Track record of promoting statistical rigour and experimental best practices in your prior roles. Prior experience using causal inference/econometric techniques and bayesian methodologies for hypothesis testing. Prior experience using large datasets with distributed computing (e.g. spark, hadoop or other map-reduce tech)Experience working ...

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 ...

shipping ML productsPhD or other experience in a research environmentDeep experience in an applicable ML area - E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clusteringStrong stats or math backgroundVisualization, data skills, SQL, matplotlib, etc. Unleash Your PotentialWhen you join Salesforce, you'll be limitless ...

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 Benefits Competitive salary and equity in a fast‐growing start‐up We serve lunch every weekday ...

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 ...

producing strong quantitative evidence to inform strategy and improve outcomes for people and communities. You will develop predictive models, apply Bayesian methods, and analyse time-series data using Python or R and SQL, translating complex findings for non-technical colleagues in a hybrid, 4-days ...

engineers, and industry experts to deliver real customer value. The role blends research and production, requiring a strong ML foundation, Bayesian methods, and ability to translate research into practical solutions. Hybrid work in London offered. #J-18808-Ljbffr ...

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 ...

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 ...

hormonal rhythms observed across individuals. To characterise this variability, you will take advantage of unique in its kind datasets and advanced mathematical and computational methods and help develop personalised models. The practical element of your project will be based on, but not limited to, time series analysis, network analysis … being welcoming and supportive. The applicant should have high proficiency with scientific computer programming in Python, Julia, R and/or MATLAB, parameter estimation methods and HPC simulations. Experience with dynamical systems theory and mathematical modelling using ODEs and/or DDEs is desirable. The vacancy ...

delivery teams within the UK Defence or Aerospace sectors. Experience in the practical application of mathematical techniques such as Monte Carlo simulation or Bayesian inference. Experience working with MoD assessment frameworks and an understanding of the UK Defence Science and Technology (S&T) landscape. Experience conducting peer … production environment. Experience working within secure environments and an understanding of the constraints of working with classified information. Expert knowledge of numerical methods, optimisation, and statistical analysis within a defence context Proficiency in mathematical programming using Python (NumPy, SciPy), FORTRAN, or Julia. Familiarity with simulation tools and synthetic environments ...

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 You5+ 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 and collaborate ...

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 ...