13 of 13 Bayesian Methods Jobs

recommendations from appropriate data sources Experience with sensor data such as Radar and various infrared sensors Experience developing and implementing probabilistic models to combine sensor data such as Bayesian reasoning, Kalman filtering and evidence theory Experience with advanced probability statistics and applying in real world scenarios Travel: 10% Drug Free Workplace: Boeing is a Drug Free Workplace More ❯

in materials discovery, computer vision, big data, or optimisation Collaborative communicator, organised, proactive, and curious Desired Skills Masters degree in ML, mathematics, or statistics Knowledge of probabilistic and Bayesian modelling Solid software-engineering principles and experience with an OO language Familiarity with cloud platforms (Azure, AWS, or GCP) and IaC tools such as Terraform More ❯

to be successful, you will have the following experience: Strong Data Analyst or Data Science background, with experience within Python and AI/ML technologies Machine learning and Bayesian modelling experience is highly desirable Experience of working with the Home Office as a customer SC Clearance is essential Within this role, you will be responsible for: Analyse 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 ❯

small- and large-scale model development. • Collaborate with engineering to deploy models in high-performance, production environments. • Publish internal technical notes or contribute to external research when appropriate. • Explore methods in synthetic data generation, foundation-model adaptation, and model compression. Your Profile • Ideally holding a Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Mathematics, Physics (or related quantitative field … learning/LLMs or adjacent advanced AI research. • Proficient in Python; experience with PyTorch or JAX. • Understanding of reinforcement learning, multi-agent systems, probabilistic/Bayesian methods, or large-scale training. • Curiosity-driven mindset, strong problem solving, and the ability to work cross-functionally. • English is the working language; additional languages are a plus. We Offer More ❯

small- and large-scale model development. • Collaborate with engineering to deploy models in high-performance, production environments. • Publish internal technical notes or contribute to external research when appropriate. • Explore methods in synthetic data generation, foundation-model adaptation, and model compression. Your Profile • Ideally holding a Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Mathematics, Physics (or related quantitative field … learning/LLMs or adjacent advanced AI research. • Proficient in Python; experience with PyTorch or JAX. • Understanding of reinforcement learning, multi-agent systems, probabilistic/Bayesian methods, or large-scale training. • Curiosity-driven mindset, strong problem solving, and the ability to work cross-functionally. • English is the working language; additional languages are a plus. We Offer More ❯

experience within predictive modelling, machine learning, and probability theory. Ideally this would be within sports or gaming/betting industries. Understanding of techniques such as Monte Carlo simulation, Bayesian modelling, GLMs, mixed effects models, time series forecasting etc Strong programming ability, preferably in Python SQL and relational databases The company offer some great benefits including a bonus More ❯

skills, and stakeholder-friendly mindset Nice to Have Experience with PowerBI , Databricks , and detection engineering tools Strong quantitative/statistical skills: confidence intervals, Monte Carlo, Bayesian methods Data tooling: Python , SQL , KQL , and experience handling large datasets Familiarity with conceptual modelling languages like ArchiMate We Offer A hybrid working model with flexibility around office days Gross More ❯

Create sophisticated customer segmentation using behavioural, transactional, and demographic data Design and build predictive models to enhance personalized customer experiences across all channels Collaborate on design of test & learn methods to measure CRM initiatives' effectiveness Monitor and optimize model performance through continuous improvement cycles Technical Implementation Transform analytical solutions into production-ready code Implement models within our existing technology … recommendations to improve customer engagement metrics Skills ? Relevant experience in Customer Marketing Data Science including applied statistics and machine learning techniques (supervised and unsupervised learning, natural language processing, Bayesian statistics, time-series forecasting, collaborative filtering etc) ? Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) ? Familiarity with cloud platforms (GCP More ❯

science libraries (NumPy, Pandas, Scikit-Learn) Experience with deep learning tools (e.g. PyTorch, TensorFlow, or similar) Strong mathematical/statistical background Familiarity with a wide range of data science methods (e.g. ML, NLP, Bayesian inference, APIs, SQL) Experience leading data science teams and managing project timelines Excellent communication and stakeholder engagement skills SC clearance/Clearable More ❯

science libraries (NumPy, Pandas, Scikit-Learn) Experience with deep learning tools (e.g. PyTorch, TensorFlow, or similar) Strong mathematical/statistical background Familiarity with a wide range of data science methods (e.g. ML, NLP, Bayesian inference, APIs, SQL) Experience leading data science teams and managing project timelines Excellent communication and stakeholder engagement skills SC clearance/Clearable More ❯

telemetry coverage. Microsoft Defender stack, Azure services, network-security fundamentals. Nice-to-Haves Hands-on experience with PowerBI, Databricks, and Detection Engineering tools. Quantitative analysis & statistics: Comfortable with statistical methods, confidence intervals and Monte-Carlo & Bayesian approaches. Data tooling: Python (data/ML stack), SQL and KQL. Able to wrangle large and dynamic data sets. Conceptual More ❯

Materials - Oxford/Remote (UK) (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We're looking for a Machine Learning Engineer to join a rapidly scaling deep-tech company that's reinventing how the world designs and … all of the following (full training provided to fill any gaps): Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, Pandas, NumPy, SciPy, CI/CD, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform, Azure, AWS, GCP, Git, and Agile methodologies. Join a team that's fusing AI, science, and engineering to push the boundaries of what's More ❯