1 to 25 of 27 Remote/Hybrid Bayesian Methods Jobs in the UK

statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability ...

statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability ...

statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability ...

statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability ...

statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability ...

statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability ...

statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability ...

statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability ...

statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability ...

statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability ...

coding skills, analytical abilities, and innovative thinking to quickly understand new domains and transform creative ideas into functional solutions. Employ statistical and data science methods to make data‐driven decisions. Manipulate large data sets for business insights and drive actionable solutions. Utilize appropriate methods and approaches to develop … Proven ability to conceptualize business problems and solve them through data science solutions. Proven knowledge of AI techniques such as Bayesian methods, Clustering, Ensemble tree models, NLP, etc., with an excellent grasp of statistical concepts and methods. Good understanding of LLMs, guardrails, RAG, agentic AI. Strong ...

natural‐world systems: messy, noisy, sparse, nonlinear, and only partially observed. Nice to Have Experience with mechanistic models, hybrid ML, Bayesian methods, causal inference, dynamical systems, or uncertainty quantification. Experience designing benchmarks in novel or poorly defined problem spaces. Experience building models that move from research ...

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 ...

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 Visualization, data skills, SQL, matplotlib, etc. Benefits We are a well treated bunch, with awesome benefits ...

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 ...

experiments, RCTs), and Multi-Touch Attribution. Hands-on experience building, validating, or calibrating MMM models- whether using Robyn, Google Meridian, PyMC-Marketing, LightweightMMM, Bayesian regression, or working closely with vendors who do. Strong foundation in causal inference and experimental design: you understand difference-in-differences, synthetic control … mindset. You thrive in ambiguity, work autonomously, and are energised by building in fast-paced, high-growth environments. Nice to haves: Experience with Bayesian modelling frameworks (TensorFlow Probability, PyMC, Stan) and their applications in marketing measurement. Familiarity with mobile analytics platforms and MMPs: Adjust, AppsFlyer, CleverTap ...

experiments, RCTs), and Multi-Touch Attribution. Hands-on experience building, validating, or calibrating MMM models- whether using Robyn, Google Meridian, PyMC-Marketing, LightweightMMM, Bayesian regression, or working closely with vendors who do. Strong foundation in causal inference and experimental design: you understand difference-in-differences, synthetic control … mindset. You thrive in ambiguity, work autonomously, and are energised by building in fast-paced, high-growth environments. Nice to haves: Experience with Bayesian modelling frameworks (TensorFlow Probability, PyMC, Stan) and their applications in marketing measurement. Familiarity with mobile analytics platforms and MMPs: Adjust, AppsFlyer, CleverTap ...

experiments, RCTs), and Multi-Touch Attribution. Hands-on experience building, validating, or calibrating MMM models- whether using Robyn, Google Meridian, PyMC-Marketing, LightweightMMM, Bayesian regression, or working closely with vendors who do. Strong foundation in causal inference and experimental design: you understand difference-in-differences, synthetic control … mindset. You thrive in ambiguity, work autonomously, and are energised by building in fast-paced, high-growth environments. Nice to haves: Experience with Bayesian modelling frameworks (TensorFlow Probability, PyMC, Stan) and their applications in marketing measurement. Familiarity with mobile analytics platforms and MMPs: Adjust, AppsFlyer, CleverTap ...

experiments, RCTs), and Multi-Touch Attribution. Hands-on experience building, validating, or calibrating MMM models- whether using Robyn, Google Meridian, PyMC-Marketing, LightweightMMM, Bayesian regression, or working closely with vendors who do. Strong foundation in causal inference and experimental design: you understand difference-in-differences, synthetic control … mindset. You thrive in ambiguity, work autonomously, and are energised by building in fast-paced, high-growth environments. Nice to haves: Experience with Bayesian modelling frameworks (TensorFlow Probability, PyMC, Stan) and their applications in marketing measurement. Familiarity with mobile analytics platforms and MMPs: Adjust, AppsFlyer, CleverTap ...

experiments, RCTs), and Multi-Touch Attribution. Hands-on experience building, validating, or calibrating MMM models- whether using Robyn, Google Meridian, PyMC-Marketing, LightweightMMM, Bayesian regression, or working closely with vendors who do. Strong foundation in causal inference and experimental design: you understand difference-in-differences, synthetic control … mindset. You thrive in ambiguity, work autonomously, and are energised by building in fast-paced, high-growth environments. Nice to haves: Experience with Bayesian modelling frameworks (TensorFlow Probability, PyMC, Stan) and their applications in marketing measurement. Familiarity with mobile analytics platforms and MMPs: Adjust, AppsFlyer, CleverTap ...

experiments, RCTs), and Multi-Touch Attribution. Hands-on experience building, validating, or calibrating MMM models- whether using Robyn, Google Meridian, PyMC-Marketing, LightweightMMM, Bayesian regression, or working closely with vendors who do. Strong foundation in causal inference and experimental design: you understand difference-in-differences, synthetic control … mindset. You thrive in ambiguity, work autonomously, and are energised by building in fast-paced, high-growth environments. Nice to haves: Experience with Bayesian modelling frameworks (TensorFlow Probability, PyMC, Stan) and their applications in marketing measurement. Familiarity with mobile analytics platforms and MMPs: Adjust, AppsFlyer, CleverTap ...

experiments, RCTs), and Multi-Touch Attribution. Hands-on experience building, validating, or calibrating MMM models- whether using Robyn, Google Meridian, PyMC-Marketing, LightweightMMM, Bayesian regression, or working closely with vendors who do. Strong foundation in causal inference and experimental design: you understand difference-in-differences, synthetic control … mindset. You thrive in ambiguity, work autonomously, and are energised by building in fast-paced, high-growth environments. Nice to haves: Experience with Bayesian modelling frameworks (TensorFlow Probability, PyMC, Stan) and their applications in marketing measurement. Familiarity with mobile analytics platforms and MMPs: Adjust, AppsFlyer, CleverTap ...

experiments, RCTs), and Multi-Touch Attribution. Hands-on experience building, validating, or calibrating MMM models- whether using Robyn, Google Meridian, PyMC-Marketing, LightweightMMM, Bayesian regression, or working closely with vendors who do. Strong foundation in causal inference and experimental design: you understand difference-in-differences, synthetic control … mindset. You thrive in ambiguity, work autonomously, and are energised by building in fast-paced, high-growth environments. Nice to haves: Experience with Bayesian modelling frameworks (TensorFlow Probability, PyMC, Stan) and their applications in marketing measurement. Familiarity with mobile analytics platforms and MMPs: Adjust, AppsFlyer, CleverTap ...

experiments, RCTs), and Multi-Touch Attribution. Hands-on experience building, validating, or calibrating MMM models- whether using Robyn, Google Meridian, PyMC-Marketing, LightweightMMM, Bayesian regression, or working closely with vendors who do. Strong foundation in causal inference and experimental design: you understand difference-in-differences, synthetic control … mindset. You thrive in ambiguity, work autonomously, and are energised by building in fast-paced, high-growth environments. Nice to haves: Experience with Bayesian modelling frameworks (TensorFlow Probability, PyMC, Stan) and their applications in marketing measurement. Familiarity with mobile analytics platforms and MMPs: Adjust, AppsFlyer, CleverTap ...

experiments, RCTs), and Multi-Touch Attribution. Hands-on experience building, validating, or calibrating MMM models- whether using Robyn, Google Meridian, PyMC-Marketing, LightweightMMM, Bayesian regression, or working closely with vendors who do. Strong foundation in causal inference and experimental design: you understand difference-in-differences, synthetic control … mindset. You thrive in ambiguity, work autonomously, and are energised by building in fast-paced, high-growth environments. Nice to haves: Experience with Bayesian modelling frameworks (TensorFlow Probability, PyMC, Stan) and their applications in marketing measurement. Familiarity with mobile analytics platforms and MMPs: Adjust, AppsFlyer, CleverTap ...