1 to 25 of 33 Permanent Bayesian Methods Jobs in London

analysis Have in depth understanding of statistical modelling/ML techniques for time series forecasting (ARIMA, ETS, Prophet, Time Series pattern detection, and ML methods) Strong experience with Causal inference, Intervention analysis, Counterfactuals Estimation, Optimization and Scenarios simulation Solid experience with Probabilistic Programming and Bayesian Methods ...

through clear documentation and transparent methodology. Ensure models meet high standards for both statistical correctness and practical applicability. Implement calibration techniques and uncertainty estimation methods where appropriate. Evaluate model behaviour under different market environments and changing economic conditions. LLM and Document Intelligence Solutions Build AI systems that extract structured … techniques. Uncertainty quantification. Model explainability methods. Handling imbalanced datasets. Missing data treatment and imputation. Distribution shift analysis. Time‐series modelling. Forecasting methodologies. Advanced Quantitative Methods Bayesian approaches. State‐space models. Regime‐switching frameworks. Hierarchical modelling. Multi‐task learning. Survival analysis. Hazard models. Event‐driven modelling. Rare ...

least 3 data or ML products from problem definition to production deployment and monitoring.* Demonstrated proficiency in clustering, predictive modeling, reinforcement learning, and Bayesian statistics.* Hands-on experience in software engineering, MLOps, and deploying machine learning models at scale.* Proficiency in SQL, Python, and familiarity with ...

Excel, and visualisation tools; experience with Databricks, Azure, or other cloud/data platforms is a plus. Deep understanding of econometrics, regression, Bayesian statistics, and advanced modelling techniques. Proven ability to handle large datasets, optimise pipelines, and deliver high-quality outputs. Track record of translating complex model ...

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 ...

technical standard for experimentation across Product Data Science, from conventional A/B testing to quasi-experimental and Bayesian methods, and make it practical through protocols, frameworks and tooling. Partner with Product, Engineering and Data Platform teams to improve experimentation velocity without sacrificing rigour. Critically assess … organisation. Statistical & Experimentation Expertise: Authoritative command of experimentation in all its forms, from experimental design and variance reduction to causal inference, bandits and Bayesian methods. You should be able to develop and validate methodology, not only apply it. Technical & Modelling Expertise: Expert level proficiency in Python and ...

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 ...

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 ...

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 ...

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 ...

with a proven record of success in online data science competitions, such as Kaggle. Experience in deep learning, reinforcement learning, non‐convex optimisation, Bayesian non‐parametrics, NLP or approximate inference. Excellent reasoning skills and mathematical ability. Strong programming skills and experience working with Python, Scikit‐Learn, SciPy ...

data pipelines using dbt, Airflow, and Snowflake. Beyond querying, you use Python for advanced automation and forecasting, and you apply statistical rigor (e.g., Bayesian statistics, causal inference) to solve complex product problems. Commercial & Risk Mindset: You possess deep commercial fluency, understanding the unit economics of a fintech ...

that ships it. You'll work closely 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). The platform is in production on a Python backend and a React ...

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 ...

teams to design and implement new statistical and machine learning features across Optimizely’s product suite. Conduct rigorous testing and validation of new statistical methods and ensure seamless integration into the platform. Analyze product performance data to optimize existing features and provide actionable recommendations for improvement. Leverage AI agents … deploy new statistical capabilities. Research and Innovation Partner with academic and industry researchers to explore cutting-edge statistical methods and machine learning innovations. Identify emerging trends in experimentation and statistics that could enhance Optimizely’s offerings. Propose and prototype advanced statistical techniques to solve challenging business problems faced ...

instinct to every sprint without being asked, and who are comfortable with problems that do not have a known answer. The work involves Bayesian statistical modeling, experiment design, and data problems with no off-the-shelf answer. Experience with agentic systems matters: understanding how model outputs feed … production handoff), working under the direction of the Tech Lead and in close partnership with the Full-stack Engineer Design, build, and validate Bayesian statistical models, time-series forecasts, and domain-specific analytical frameworks (marketing mix models, brand equity models, price elasticity and promotional lift models) that ...

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 ...

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 ...

built that other people went on to use Broad training in empirical method, potentially from a field outside machine learning – experimental design, Bayesian inference, model selection, significance testing, uncertainty quantification Experience with automated grading and model-based judging, and a rigorous account of its failure modes and ...

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 ...

organisation. Statistical & Experimentation Expertise: Authoritative command of experimentation in all its forms, from experimental design and variance reduction to causal inference, bandits and Bayesian methods. You should be able to develop and validate methodology, not only apply it. Technical & Modelling Expertise: Expert level proficiency in Python and … and growth over time, and to bring that perspective into how experiments are designed and interpreted. Standardising at Scale: Experience standardising processes, frameworks or methods across multiple teams, including the use of AI and automation to make good practice the default. Cross‐Functional Partnership: Proven ability to build strong ...

velocity, and tackle complex scenarios where traditional A/B tests fall short. You will build robust metric systems, apply Bayesian methods and multi-arm bandits, and mentor junior data scientists while ensuring products scale safely across markets and time. #J-18808-Ljbffr ...

and strategic level. Experience delivering marketing analytics e.g., Marketing Mix Modeling , geo experiments, meta-analysis, audience segmentation and propensity modeling . Understanding of Bayesian approaches and modeling frameworks. Proven ability to generate practical solutions for marketing analytics problems and use results to drive business change in partnership … talent. Responsibilities Provide support in media strategy, measurement and optimization that require expertise in advanced analytics work, with special focus on marketing analytics methods and data science. Partner with internal teams in advanced analytics work including experimentation, measurement and modeling. Identify patterns and behaviors that are effective predictors ...

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 ...

order to improve Eligible to work in London. And any of these would be great, but aren’t essential: Experience in applying machine learning methods to real-world problems Familiarity with supervised ML Familiarity with Time Series Forecasting Familiarity with supervised LLM chat and workflow automation Familiarity with Computer … Vision Familiarity with Bayesian Learning Familiarity with Causal Inference Familiarity with Recommender Systems Familiarity with Graphs and GNNs Familiarity with Reinforcement Learning Familiarity with Apache Spark or other distributed processing frameworks A paid 6-week sabbatical leave after four years For everyone, everywhere. We’re people building ...