1 to 25 of 27 Permanent Bayesian Methods Jobs in London

Economics, Engineering etc.) Knowledge of advanced statistical concepts and techniques, e.g. skilled in linear algebra. Experience conducting hands-on analytics projects using advanced statistical methods such as generalized regression models, Bayesian methods, random forest, gradient boosting, neural networks, machine learning, clustering, or similar methodologies. Proficiency ...

from prototype through to operational deployment. Core Technical Skills Candidates should demonstrate strength in several of the following areas: Statistical modelling Probabilistic modelling Bayesian inference Forecasting Machine learning Simulation modelling Agent‐based modelling Optimisation techniques Experimental design Synthetic data generation Decision science Scenario analysis As important ...

digital businesses. Experience with Snowflake, Power BI, Tableau or similar analytics tools. Exposure to attribution modelling, marketing mix modelling (MMM), Bayesian methods, or advanced experimentation frameworks. Work Shift Western Union values in‐person collaboration, problem solving, and ideation whenever possible. We believe this fosters common ways ...

digital businesses.* Experience with Snowflake, Power BI, Tableau or similar analytics tools.* Exposure to attribution modelling, marketing mix modelling (MMM), Bayesian methods, or advanced experimentation frameworks.**Work Shift**Western Union values in-person collaboration, problem solving, and ideation whenever possible. We believe this fosters common ways ...

Excel, and visualisation tools; experience with Databricks, Azure, or other cloud/data platforms is a plus. Strong understanding of econometrics, regression, Bayesian statistics, and advanced modelling techniques. Skilled in handling large datasets, optimising pipelines, and delivering high-quality outputs Track record of translating complex model results ...

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 ...

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 ...

Challenge - Winners, multiple Best Paper Awards, and industry recognition. This role focuses on advancing the state-of-the-art in reinforcement learning (RL), Bayesian optimisation (BO), AI agents, large language models (LLMs), and vision-language models (VLMs). Whether your strength lies in fundamental algorithmic research ...

broader Drug Development organization. Key responsibilities of this position are focused on four areas: Active engagement with stakeholders and driving development of statistical methods and research. Providing statistical consulting to specific projects. Overseeing development of tools and software to implement methodological solutions. Mentoring and coaching junior members … required component of this position as they will engage with Biostatisticians and other cross-functional team members to drive development of innovative statistical methods for emerging trial design and analytics problems. Key Responsibilities Drives formulation, development and implementation of innovative novel statistical analysis methods and innovative study designs ...

exposure to tools such as Meridian, Robyn, or PyMC Proficiency in Python and experience working with cloud platforms such as GCP Understanding of Bayesian statistics and marketing attribution concepts Ability to communicate technical findings clearly to non-technical audiences Interest in applying AI tools to enhance data ...

Python and experience working with open-source MMM frameworks such as Meridian, Robyn, or PyMC Solid understanding of statistical modelling techniques, including Bayesian approaches Experience delivering analytical work in a client-facing or stakeholder-driven environment Ability to assess model quality and clearly communicate findings ...

with time‐series modelling and industrial or IoT data. You have experience in any of: dynamical systems, reinforcement learning, system identification, optimisation or Bayesian statistics. You are used to working in a fast‐paced startup environment with an agile process. You have a degree in machine learning ...

right — not just delivering an output. Technically Proficient: You are experienced in Python and comfortable working with GCP, with a solid understanding of Bayesian statistics and marketing attribution concepts. A Practical AI User: You use AI tools in your day‐to‐day work, with a habit ...

Proficiency in Python with experience using open-source MMM frameworks such as Meridian, Robyn, or PyMC Solid grounding in statistical modelling, including Bayesian approaches and media attribution Proven experience working in a client-facing environment, delivering insights to senior stakeholders Experience leading or mentoring data scientists while ...

produce rigorous analyses and clearly communicate findings for media decisions. The role requires hands-on expertise in Marketing Mix Modelling, Python, and Bayesian statistics, with a practical approach to applying AI to workflows. #J-18808-Ljbffr ...

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 ...

work with product and engineering priorities. Nice to have Experience quantifying uncertainty in large models — calibration and confidence estimation via Bayesian methods, ensembling, steering, or prompt-based approaches. Experience with machine translation, multilingual NLP, or document-/layout-aware modelling experience. Familiarity with MoE-specific training ...

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 ...

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 ...

design experiments, model customer behaviour, analyse large datasets across the funnel, and collaborate with commercial, strategy and product colleagues. Experience with causal inference, Bayesian thinking, and AI-driven analytics is highly valued. #J-18808-Ljbffr ...

continuously learn and improve Desirable: Study design and sample size experience Regulatory experience A basic understanding or willingness to learn Bayesian methods and causal inference modelling Experience within Oncology and/or CNS therapeutic areas Opportunities at Veramed Presenting at conferences and authoring publications Developing and ...

continuously learn and improve Desirable: Study design and sample size experience Regulatory experience A basic understanding or willingness to learn Bayesian methods and causal inference modelling Experience within Oncology and/or CNS therapeutic areas Opportunities at Veramed Presenting at conferences and authoring publications Developing and ...

unclear. You should apply if... You have deep expertise across a range of ML techniques (e.g. Transformer‐based NLP, Deep Learning, Tree‐based methods, Bayesian modelling) and the judgment to select solutions that balance theoretical soundness against engineering practicality. You have a proven track record ...

helps and where it doesn’t. The requirements Essential: Statistical foundations . Strong grounding in probability and statistics, with an understanding of Bayesian reasoning and experience applying hierarchical modelling or decision-making under uncertainty. Causal inference . Experience separating signal from noise in observational and experimental data. … different audiences. Bonus: Modelling depth . Experience building or adapting statistical or ML models, with an interest in understanding what’s happening underneath. Stochastic methods . Familiarity with stochastic modelling concepts as they apply to inference, time series, or uncertainty. Funnel and marketplace experience . Experience with conversion funnel ...

performance, and memory utilization across heterogeneous hardware clusters using expressive hardware DSLs (e.g., TileLang, Triton). Advance the LLM orchestration loop and leverage Bayesian optimization to automate the search, generation, and continuous improvement of high-performance NPU kernels. Key Responsibilities Design and execute scaled RL finetuning workflows … focus on Machine Learning. Deep proficiency in PyTorch and experience writing custom training loops and data pipelines. Hands-on experience with RLHF/RLVF methods (e.g., PPO, GRPO) and an understanding of policy optimization dynamics. Technical familiarity with at least two of the following: DeepSpeed, FSDP, verl or trl. ...