11 of 11 Bayesian Methods Jobs

user interface for trading analytics requirements in the Fixed Income Finance business. Create, implement, and support quantitative models for the Fixed Income trading business, leveraging mathematical and computer science methods including mathematical finance, statistics, probability, and software engineering. Design database structures and write SQL and KDB queries for data manipulation and retrieval, including creating, updating, and optimizing database schemas … calculating Risk Weighted Asset and Global Systemically Important Bank score. Proven ability to calculate return on Tangible Common Equity for the Fixed Income Finance business. Expertise in applying statistical methods, including linear programming and time series analysis, to build mathematical optimizers and predictive models. Proficiency in Convex Optimization, Monte-Carlo methods, Bayesian estimation, Stochastic modelling … critical firm-wide metrics such as RWA, G-SIB, and TCE for the Fixed Income Finance business. Advanced Quantitative Development: Apply and develop expertise in mathematical optimization, advanced statistical methods, and quantitative modelling for complex financial instruments. Full-Stack & Automated Solutions: Lead the design and implementation of automated systems and full-stack platforms, from pricing to interactive user interfaces. More ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯