1 to 25 of 26 Remote Bayesian Methods Jobs

understanding of statistical modelling/ML techniques Experience with Regression based models applied to the context of MMM modelling Solid experience with Probabilistic Programming and Bayesian Methods Be an expert in mining large & very complex data sets using SQL and Spark Have in depth understanding of statistical modelling techniques and their mathematical foundations, Have a good More ❯

opportunity to extend long-term. This is an exciting opportunity to join a high-performing Data Science team focused on advancing marketing effectiveness through advanced econometric modelling—including Bayesian Marketing Mix Modelling (MMM), Multi-Touch Attribution (MTA), and data-driven optimization strategies. Key Responsibilities Lead and manage data workflows: data extraction, transformation, validation, and exploratory analysis to … ensure modelling-readiness. Build and refine Bayesian MMM models that capture the drivers of key marketing and commercial KPIs. Use Python (and optionally R) to design, build, and improve base and advanced models—integrating prior knowledge, probabilistic reasoning, and real-world constraints. Develop and present ROI workbooks, response curves, and optimization frameworks for marketing budget allocation. Run … test models, identifying opportunities for improvement and ensuring robustness, interpretability, and business relevance. Requirements Extensive experience in building and deploying Marketing Mix Models, with a strong focus on Bayesian methods. Expert-level proficiency in Python, especially with pandas, NumPy, and probabilistic programming libraries such as PyMC. Experience with R is a bonus, particularly for MMM-related workflows. More ❯

libraries of predictive features and probabilistic representations for diverse ML tasks. Build and optimize tools for scalable probabilistic inference under memory, latency, and compute constraints. Apply and innovate on methods like Bayesian neural networks , variational autoencoders , diffusion models , and Gaussian processes for modern AI use cases. Collaborate closely with product, engineering, and business teams to build … trends in generative modeling, causality, uncertainty quantification, and responsible AI. Requirements/Qualifications: Strong experience in Bayesian inference and probabilistic modeling : PGMs, HMMs, GPs, MCMC, variational methods, EM algorithms, etc. Proficiency in Python (must) and familiarity with PyMC, NumPyro, TensorFlow Probability , or similar probabilistic programming tools. Hands-on experience with classical ML and modern techniques, including … deep learning , transformers , diffusion models , and ensemble methods . Solid understanding of feature engineering, dimensionality reduction, model construction, validation, and calibration. Experience with uncertainty quantification and performance estimation (e.g., cross-validation, bootstrapping, Bayesian credible intervals). Familiarity with database and data processing tools (e.g., SQL, MongoDB, Spark, Pandas). Ability to translate ambiguous business problems into More ❯

stakeholders and translating research into practical solutions for predictive analytics. Experience in solution design, architecting and outlining data analytics pipelines and flows. Advanced Mathematics skills including experience with Bayesian statistics, linear algebra and MVT calculus, advanced data modelling and algorithm design experience. Design and deployment experience using Tensor Flow, Spark ML, CNTK, Torch or Caffe. The perks More ❯

is essential. Experience with Regression based models in an MMM context. Strong understanding of statistical modelling/Machine Learning techniques. Experience with probabilistic programming and Bayesian methods Good working knowledge of cloud-based data science frameworks. This is a 6 month contract position which provides a daily rate of £688 (Inside IR35). In terms of More ❯

is essential. Experience with Regression based models in an MMM context. Strong understanding of statistical modelling/Machine Learning techniques. Experience with probabilistic programming and Bayesian methods Good working knowledge of cloud-based data science frameworks. This is a 6 month contract position which provides a daily rate of £688 (Inside IR35). In terms of More ❯

teams to design, implement, and optimize data pipelines and predictive models that inform trading decisions and enhance operational efficiency. RESPONSIBILITIES: Primary Focus: Probabilistic Weather Modelling: Research and prototype probabilistic methods (Bayesian inference, state-space filtering, change-detection tests, etc.) that flag when fresh weather guidance materially diverges from prior outlooks. Continuous Development and Improvement: Calibrate confidence … of a degree in Statistics, Applied Maths, Physics or related field. Minimum of 2 years working in a Data Science related role Proven depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory). Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). More ❯

teams to design, implement, and optimize data pipelines and predictive models that inform trading decisions and enhance operational efficiency. RESPONSIBILITIES: Primary Focus: Probabilistic Weather Modelling: Research and prototype probabilistic methods (Bayesian inference, state-space filtering, change-detection tests, etc.) that flag when fresh weather guidance materially diverges from prior outlooks. Continuous Development and Improvement: Calibrate confidence … of a degree in Statistics, Applied Maths, Physics or related field. Minimum of 2 years working in a Data Science related role Proven depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory). Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). More ❯

Expertise in using data visualization tools such as Google Looker and working with Google's BigQuery. Experience in design and evaluation of A/B tests. Familiarity with Bayesian statistics, especially for hypothesis testing. Extra points for good knowledge of Bayesian programming (PyMC3, etc). Experience with application of optimization theory or reinforcement learning More ❯

Understand complex and critical business problems, formulates integrated analytical approach to mine data sources, employ statistical methods and machine learning algorithms to contribute solving unmet medical needs, discover actionable insights and automate process for reducing effort and time for repeated use. To manage the implementation and adherence to the overall data lifecycle of enterprise data from data acquisition or … biostatistics, or other quantitative field (or equivalent). More than 3 years experience in clinical drug development with extensive exposure to clinical trials. Strong knowledge and understanding of statistical methods such as time to event analysis, machine learning, meta-analysis, mixed effect modeling, longitudinal modeling, Bayesian methods, variable selection methods (e.g., lasso, elastic net More ❯

Skills and Experience Strong academic background, with a degree in Computer Science (2:1 and above). Strong numerical background with a knowledge of key statistical principals e.g. Bayesian and frequentist statistics, probability distributions. Fundamental understanding of ML algorithms e.g. linear and logistic regression, random forest, neural networks, time series models. Experience with multiple programming languages, with More ❯

doing causal inference/segmentation Ability to explain ideas and present results to non-technical audiences Strong stakeholder management skills Experience with marketing mix models and/or Bayesian time series would be a big plus Strong theoretical understanding and experience with key classification and regression models is a plus Please note this role is offered on … doing causal inference/segmentation Ability to explain ideas and present results to non-technical audiences Strong stakeholder management skills Experience with marketing mix models and/or Bayesian time series would be a big plus Strong theoretical understanding and experience with key classification and regression models is a plus Please note this role is offered on More ❯

Understands complex and critical business problems from a variety of stakeholders and business functions, formulate integrated analytical approach to mine data sources, employ statistical methods and machine learning algorithms to contribute solving unmet medical needs, discover actionable insights and automate process for reducing effort and time for repeated use. To manage the definition, implementation and adherence to the overall … biostatistics, or other quantitative field (or equivalent). More than 6 years experience in clinical drug development with extensive exposure to clinical trials. Strong knowledge and understanding of statistical methods such as time to event analysis, machine learning, meta-analysis, mixed effect modeling, longitudinal modeling, Bayesian methods, variable selection methods (e.g., lasso, elastic net More ❯

existing results in the broad field of machine learning. You will be apart of a highly unique research group across Natural Language Processing, Large Learning Models, deep learning, Bayesian & Signal Optimization with the exciting transition to the world of financial predication through the prism of machine learning. The most exceptional team members combine strong technical skills and More ❯

existing results in the broad field of machine learning. You will be apart of a highly unique research group across Natural Language Processing, Large Learning Models, deep learning, Bayesian & Signal Optimization with the exciting transition to the world of financial predication through the prism of machine learning. The most exceptional team members combine strong technical skills and More ❯

libraries like mplsoccer . Advanced MLOps & Modelling: Deeper experience with the Vertex AI lifecycle (especially Pipelines ) and advanced modelling techniques relevant to football (player valuation, tactical analysis). Bayesian Modelling: Experience with probabilistic programming (e.g., PyMC). Stakeholder Management: Proven success working directly with business stakeholders to define and deliver impactful solutions. What They Offer Work that More ❯

libraries like mplsoccer . Advanced MLOps & Modelling: Deeper experience with the Vertex AI lifecycle (especially Pipelines ) and advanced modelling techniques relevant to football (player valuation, tactical analysis). Bayesian Modelling: Experience with probabilistic programming (e.g., PyMC). Stakeholder Management: Proven success working directly with business stakeholders to define and deliver impactful solutions. What They Offer Work that More ❯

Science, Engineering, Statistics, Economics, Mathematics, or a related technical or quantitative field, or equivalent practical experience. Nice to have: Experience with advanced experimentation methodologies (e.g., Bayesian methods, multi-armed bandits, causal inference). Experience specifically building or managing platforms for internal developers/users. Proven track record of successfully scaling experimentation programs and culture within an More ❯

and implementing advanced mathematical models that drive the ToffeeX engineering design software. You will collaborate with a multidisciplinary team to solve complex engineering problems, focusing on mathematical optimization, numerical methods for partial differential equations (PDEs), and computational geometry. This role offers the opportunity to work at the intersection of advanced mathematics, engineering, and technology in a rapidly growing company. … literature, developing creative approaches to solve unique real-world engineering problems. Essential Skills & Experience Ph.D. in Applied Mathematics, Physics, Engineering, or a closely related field. Research level experiencein numerical methods for PDEs, mathematical modelling or PDE-constrained optimization. Hands-on experience in developing and implementing numerical algorithms for solving complex simulation or optimization problems. You thrive in a fast … for physical systems. Experience in numerical optimization topics such as nonconvex, robust, or Bayesian optimization. Experience with topology or shape optimization. Experience with AI/ML methods for physics or optimization problems. Experience with software development in C++, Python, or similar languages. Company Benefits Flexibility and support for continuous learning and professional growth. 25 days holiday More ❯

Physics, or similar). Experience building and maintaining predictive credit models. Fluency in Python (Pandas, NumPy, SciPy, Matplotlib) and SQL. Experience with advanced modelling techniques (e.g., Monte Carlo, Bayesian modelling) is a plus. Strong communicator. Commercial mindset and strong instincts around risk and return. Experience mentoring or managing analysts. Knowledge of the German lending market or language More ❯

Physics, or similar). Experience building and maintaining predictive credit models. Fluency in Python (Pandas, NumPy, SciPy, Matplotlib) and SQL. Experience with advanced modelling techniques (e.g., Monte Carlo, Bayesian modelling) is a plus. Strong communicator. Commercial mindset and strong instincts around risk and return. Experience mentoring or managing analysts. Knowledge of the German lending market or language More ❯

Physics, or similar). Experience building and maintaining predictive credit models. Fluency in Python (Pandas, NumPy, SciPy, Matplotlib) and SQL. Experience with advanced modelling techniques (e.g., Monte Carlo, Bayesian modelling) is a plus. Strong communicator. Commercial mindset and strong instincts around risk and return. Experience mentoring or managing analysts. Knowledge of the German lending market or language More ❯

importantly, impact patients' lives. Opportunity We're now hiring a Director of Statistical Genetics & Functional Genomics to lead a growing team that integrates human genetics, functional genomics, and computational methods to drive novel target discovery. This is a rare opportunity to help shape our therapeutic pipeline by unlocking the causal mechanisms of disease from human data. Your responsibilities Lead … architecture. Collaborate cross-functionally with disease biology, target discovery, and experimental teams to translate genetic insights into testable hypotheses and novel therapeutic concepts. Stay at the forefront of emerging methods in statistical genetics and variant-to-function inference, guiding internal adoption and development. Contribute to platform strategy and target identification efforts across multiple disease areas. Foster a culture of … and supporting their continued development. Who you are You bring deep expertise in human statistical genetics, including fine-mapping, LD structure, polygenic risk scoring, partitioned heritability, and causal inference methods (e.g. Mendelian Randomisation). You have experience integrating multi-modal data-including GWAS, transcriptomic (bulk and single-cell), epigenomic (ATAC-seq, ChIP-seq), and proteomic datasets-to identify causal More ❯

testing and test statistics Highly numerate and data-driven Excel skills (can maintain complex spreadsheets) Experience analysing customer trends and behaviours Good understanding of frequentist and/or Bayesian analysis methodologies Additional Information Benefits package includes: Hybrid working Great compensation package and discretionary bonus Core benefits include pension, bupa healthcare, sharesave scheme and more 25 days annual More ❯

testing and test statistics Highly numerate and data-driven Excel skills (can maintain complex spreadsheets) Experience analysing customer trends and behaviours Good understanding of frequentist and/or Bayesian analysis methodologies Additional Information Benefits package includes: Hybrid working Great compensation package and discretionary bonus Core benefits include pension, bupa healthcare, sharesave scheme and more 25 days annual More ❯