1 to 25 of 27 Bayesian Methods Jobs

least 3 data or ML products from problem definition to production deployment and monitoring. Demonstrated proficiency in clustering, predictive modeling, reinforcement learning, and Bayesian statistics. Hands-on experience in software engineering, MLOps, and deploying machine learning models at scale. Proficiency in SQL, Python, and familiarity with ...

with our AIOps engineering teams to productionize and scale analytical capabilities beyond traditional manual analysis. By leveraging your deep understanding of marketing data, statistical methods, and emerging AI technologies, you'll enable data-driven marketing strategies that maximize ROI and competitive advantage. Develop and maintain econometric models to measure … budget allocation Hands-on experience working with Google Analytics data and other marketing platforms Experience with marketing mix modelling, incrementality testing, and causal inference methods Familiarity with marketing data sources and platforms (Facebook Ads, programmatic platforms, etc.) Strong knowledge of experimental design and statistical modelling techniques including regression analysis ...

build datasets suited for modelling and in-depth analysis. Design and execute measurement frameworks— including A/B testing, causal impact analysis, and multivariate methods— selecting the appropriate technique based on the business question and clearly communicating trade-offs. Build, evaluate, and iterate on statistical models (e.g., regression, clustering … analytics, or a related domain. Familiarity with big data querying tools such as Presto, Hive, BigQuery, or Hadoop. Exposure to Bayesian methods, causal inference, or multi‐armed bandit approaches. Experience collaborating with Machine Learning or Data Science teams to validate and scale models for business impact. ...

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 ...

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 ...

detection", etc Analyse data to help in better decision making Supporting initiatives for data integrity and normalization Data mining using state‐of‐the‐art methods Doing ad‐hoc analysis and presenting results in a clear manner Managing and designing the reporting environment, including data sources, security, and metadata Qualifications … Machine learning development projects Job Skills & Responsibilities: Experience in machine learning Exposure to machine learning models and corresponding statistics like K‐means, Bayesian, Clustering Strong technical skills with Python along with NumPy, Pandas, Scikit‐Learn Machine learning experience -> predictive and prescriptive modelling Data wrangling and data cleansing ...

table and define new AI opportunities within the business. Skills and Experience Strong track record in machine learning, NLP, and AI application-Bayesian modeling is a plus Proficient in Python (preferred), R, or similar languages and ML frameworks (e.g., TensorFlow, PyTorch) Exceptional analytical and problem-solving skills ...

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 ...

stakeholder-facing xnkfpon role Nice to Have Experience in consulting, analytics advisory, or agency environments Knowledge of causal inference, time-series modelling, or Bayesian approaches Experience with data visualisation tools such as Tableau or Power BI Experience working with large and complex marketing datasets What the Company ...

data stack—from processing raw sequencing (omics) to interpreting the physics and geometry of macromolecular structures. Closed‐loop Discovery: Experience in Active Learning, Bayesian Optimization, or Optimal Experimental Design. Systems Engineering: Experience training and deploying large‐scale models or managing complex multi‐agent orchestrations. Causal Inference: Experience ...

engineers • Some front-end/product sense (you care about shipping usable tools, not just notebooks) • Experience with causal inference, Bayesian methods, or mechanistic simulation ...

supervision activities in the field of Statistics and Machine Learning at Institute for Statistics and Mathematics which also features a strong group in Bayesian statistics, see . We are particularly interested in researchers whose scientific work focuses on the methodological aspects of modern statistical techniques and machine ...

data pipelines using dbt, Airflow, and Snowflake. Beyond querying, you use Python for advanced automation and forecasting, and you apply statistical rigor (e.g., Bayesian statistics, causal inference) to solve complex product problems. Commercial & Risk Mindset: You possess deep commercial fluency, understanding the unit economics of a fintech ...

seeking a skilled Machine Learning Scientist for its London Research Centre. The role centers on advancing AI technologies, particularly in reinforcement learning and Bayesian optimisation. Successful candidates will have a PhD in Computer Science and a strong publication record in top-tier ML venues. This opportunity involves ...

possess deep expertise in lifetime value (LTV) modelling and econometrics/marketing mix modelling, complemented by a strong understanding of statistics, particularly Bayesian reasoning, which enables you to accurately estimate results and know when to deliver actionable insights. Your technical toolkit includes experience with Bayesian ...

Experience we're interested in: Conformal prediction, conformal inference, uncertainty quantification and statistical learning theory Probabilistic modelling, online learning, or Bayesian methods Ideal experience: Foundation models, generative AI, or multi-agent systems PyTorch, JAX, and large-scale ML systems ...

edge algorithms that combine scientific and applied innovation. Candidates should have a strong academic background in Computer Science, expertise in reinforcement learning or Bayesian optimisation, and proficiency in Python. This is an exciting opportunity to contribute to high-impact AI projects within a dynamic multinational team. #J ...

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 ...

shelf AI. This organisation has built its reputation on proprietary Bayesian tools and deep scientific capability, using advanced sampling methods and modern AI technologies to tackle problems that standard approaches cant. If you enjoy difficult technical challenges, rigorous thinking and working at the intersection of research … Bayesian data science tools, while using modern LLM and GPT-based tools to enhance and accelerate your workflow Explore new models, methods and technologies, applying them where they add genuine value Contribute to the development of the companys core scientific and technical capabilities Collaborate with clients ...

shelf AI. This organisation has built its reputation on proprietary Bayesian tools and deep scientific capability, using advanced sampling methods and modern AI technologies to tackle problems that standard approaches can’t. If you enjoy difficult technical challenges, rigorous thinking and working at the intersection … Bayesian data science tools, while using modern LLM and GPT-based tools to enhance and accelerate your workflow Explore new models, methods and technologies, applying them where they add genuine value Contribute to the development of the company’s core scientific and technical capabilities Collaborate with ...

Bayesian reasoning, hypothesis testing, probability distributions, and uncertainty quantification. Experience with causal inference, probabilistic graphical models, survival analysis, or similar methods for analyzing sequential or time dependent processes. Comfort working with large, complex, and imperfect datasets - you know how to validate, clean, and reason critically about ...

Build production grade Python packages. Follow and build project scaffolds (PowerShell), follow coding standards, and reproducible workflows. Transform analyses into standardized currently best known methods (cBKM). Process data and automate data flows; manage and optimize data structure & databases for big data sets. Interact with product and service teams … Bachelor or Master Degree: Statistics/Computer Science/Data Science/Industrial Engineering Expert knowledge of Python, statistical modelling (frequentist and Bayesian) and data visualization Intermediate knowledge of PowerShell, R and SQL AI expert knowledge Project management Comfortable with non recurrent, high complexity engineering analyses that ...

Build production-grade Python packages. Follow and build project scaffolds (PowerShell), follow coding standards, and reproducible workflows. Transform analyses into standardized currently best-known methods (cBKM) Process data and automate data flows; manage and optimize data structure & data bases for big data sets. Interact with product and service teams … Bachelor or Master Degree: Statistics/Computer Science/Data Science//Industrial Engineering Expert knowledge of Python, statistical modelling (frequentist and Bayesian) and data visualization Intermediate knowledge of PowerShell, R and SQL AI expert knowledge Project management Comfortable with non-recurrent, high-complexity engineering analyses ...

grow and you to mentor. What you bring to the table Enthusiasm about using machine learning, especially deep learning and/or probabilistic methods, for science and engineering. Ability to scope and effectively deliver projects. Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend … applied statistics, mathematics, physics, engineering, or a related field, with particular expertise in any of the following: operator learning (neural operators), or other probabilistic methods for PDEs; geometric deep learning or other 3D computer vision methods for point‐cloud or mesh‐structured data; generative models for geometry and ...

bring to the table Ability to scope and effectively deliver projects. Enthusiasm about using machine learning, especially deep learning and/or probabilistic methods, for science and engineering. Strong problem‐solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly. Excellent collaboration and communication skills … applied statistics, mathematics, physics, engineering, or a related field, with particular expertise in any of the following: operator learning (neural operators), or other probabilistic methods for PDEs; geometric deep learning or other 3D computer vision methods for point‐cloud or mesh‐structured data; generative models for geometry and ...