1 to 25 of 47 Bayesian Methods Jobs

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 ...

Overview At EIT we are seeking an experienced and detail oriented Senior or Non Senior Scientist with recognised expertise in developing computational methods and algorithms for genomic sequencing data analysis. This is an exciting opportunity to develop novel computational approaches for microbial data that will become part … platform teams to deliver scientifically rigorous, scalable, and clinically relevant innovation in the microbial genomics space. Key Responsibilities Design, develop and evaluate novel computational methods in areas such as genome assembly, binning, and functional characterisation of genomes from metagenomic sequencing data. Collaborate with scientists across EIT to apply ...

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 ...

cases as well as models. Train Machine Learning Models: Use machine learning and statistical modelling techniques such as recommendations, reinforcement learning, decision trees, Bayesian analysis, neural networks and transformers to develop and evaluate algorithms to address business use cases and/or to improve product/system ...

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 ...

priors) into calibrated probability estimates. Build pricing and edge frameworks: fair value, uncertainty bands, expected value, and model drift/regime diagnostics. Design evaluation methods (proper scoring rules like log loss/Brier score, calibration curves, back-tests with realistic costs and constraints). Trading & Market Design (Applied) Identify … with SQL; experience with streaming systems (Kafka), workflow orchestration (Airflow), and cloud (AWS/GCP/Azure). Experience with Bayesian methods, probabilistic programming (Stan/PyMC), or ensemble methods. Familiarity with rigorous experimentation: online/offline evaluation, data leakage prevention, and model governance. Tech Stack ...

Nuclear Engineering Data Scientist: Develop and deploy machine learning models, including deep neural networks (DNNs), convolutional neural networks (CNNs), and Bayesian neural networks (BNNs), to solve nuclear engineering problems. Design hybrid modeling frameworks that combine physics-based and data-driven approaches for applications such as critical heat … flux prediction and reactor physics simulations. Implement uncertainty quantification techniques, such as ensembling and Bayesian methods, to ensure robust and reliable predictions in nuclear systems. Optimize nuclear engineering processes using advanced AI methodologies, including transfer learning and generative models. Collaborate with cross-functional teams to integrate ...

cases as well as models. Train Machine Learning Models: Use machine learning and statistical modelling techniques such as recommendations, reinforcement learning, decision trees, Bayesian analysis, neural networks and transformers to develop and evaluate algorithms to address business use cases and/or to improve product/system ...

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 ...

with strong foundations, deep structured‐data experience, and the judgement to apply the right level of complexity – from simple, robust baselines to more advanced methods where they add clear value. Key Responsibilities What will you be doing? Our direction of travel includes: Early-warning and lifecycle modelling. For rent … Time Time‐to‐event and state‐transition approaches (e.g. discrete‐time classification, roll‐rate models) for lifecycle and hazard problems. Forecasting using classical statistical methods, Bayesian/state‐space approaches, and modern pretrained time‐series foundation models. Connecting Models to Real Decisions Framing problems like contact ...

with exposure to statistical modelling or Marketing Mix Modelling Proficiency in Python and experience working with cloud platforms such as GCP Understanding of Bayesian statistics and marketing attribution methodologies Experience with tools such as Meridian, Robyn, PyMC, or similar modelling frameworks Ability to communicate complex technical findings ...

and/or R, with strong data analysis and visualization skills and a firm grasp of modern statistics (mixed models, Bayesian methods, etc.) Experience building reproducible and well-documented analysis workflows (Nextflow, Snakemake) and applying sound data organization and metadata practices Demonstrated ability to champion cross ...

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 ...

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/ ...

Looking For Experience with Marketing Mix Modelling or statistical modelling Strong Python skills and experience working with large datasets Understanding of Bayesian statistics and attribution methodologies Experience with tools such as Meridian, Robyn, PyMC, or similar Ability to communicate technical findings clearly to stakeholders Strong attention ...

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 ...

required to obtain UK Security Clearance. Desirable Experience Experience with any of the following would be beneficial: Statistical modelling, Bayesian methods, uncertainty estimation, or probabilistic techniques. Synthetic data generation, multi-modal AI, or action recognition. Machine learning development tools, experiment tracking, dataset management, or CI/ ...

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 ...

Analyst or Data Scientist Minimum 2:1 in a Quantitative subject ideally Masters Experience OR an interest in Modelling – CHAID, Cluster Analysis, Bayesian Algorithms, NN, Experience with visualisation tools would be nice Python and SQL experience ideally - Python a MUST Experience in a Data Science role with ...

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 ...