1 to 25 of 38 Bayesian Methods Jobs

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 ...

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 ...

intellectually curious, analytical, and passionate about understanding cause-and-effect relationships in complex systems. You bring strong quantitative skills and enjoy applying rigorous methods to high-impact business challenges.Experience applying causal inference techniques in a commercial, product, marketing, or research environment.Strong understanding of causal inference methods. Exposure to experimental … such as Double Machine Learning, Causal Forests, Meta-Learners, and Uplift Models.Experience evaluating incrementality, or uplift using experimental data.Knowledge of Bayesian methods for causal analysis and decision-making.Experience in gaming, e-commerce, or subscription-based products.Experience working with large-scale data using PySpark or equivalent distributed ...

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 ...

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 ...

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 ...

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 ...

calculations, choosing the right unit of randomisation, guardrail metrics, interpreting inconclusive results.You have a proficient understanding of statistics — sample size, variance, multiple-comparisons, Bayesian reasoning.You know how to measure the incremental impact of ML models and CRM interventions end-to-end — defining success and guardrail metrics, designing ...

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/ ...

Stats Background • Outstanding background in probability and statistics • Experience and interest in modern machine learning techniques, for example, deep learning, Bayesian methods and graphical models • Programming experience with python, julia or R You will be joining a progressive and exciting company committed to excellence. They offer ...

choosing the right unit of randomisation, guardrail metrics, interpreting inconclusive results. You have a proficient understanding of statistics — sample size, variance, multiple-comparisons, Bayesian reasoning. You know how to measure the incremental impact of ML models and CRM interventions end-to-end — defining success and guardrail metrics ...

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 ...

with other research teams in Alphabet. AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation. In this hybrid role, you will report to a Senior Staff Software Engineer. You will: Partner with ...

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/ ...

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 ...

markets (e.g. UK and Germany). Regulatory submission experience in key markets (e.g. EU and USA). Application of indirect comparison methodology (e.g. Bayesian/Frequentist NMA and MAIC/STC methodologies). Experience of performing adjustment for treatment switching/cross‐over within clinical trials (e.g. ...

Stats or Engineering degree.Outstanding background in probability and statisticsExperience and interest in modern machine learning techniques, for example, deep learning, Bayesian methods and graphical modelsProgramming experience with python, julia or RYou will be joining a progressive and exciting company committed to excellence. They offer an excellent ...

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 ...

into a compelling product vision and strategic roadmap. Deep expertise in advanced measurement techniques including Marketing Mix Modeling (MMM) (including various methodologies like Bayesian), Multi-Touch Attribution (MTA), Incrementality testing, and marketing experimentation. Strong understanding of marketing data sources, data ingestion, transformation, and reporting challenges. Deep expertise ...