1 to 25 of 27 Bayesian Methods Jobs

working as a contractor in fast-paced project settings Nice to Have Experience working with large brands or multi-market models Familiarity with Bayesian MMM or advanced econometric approaches Experience with cloud data platforms or marketing analytics tools Background in retail, FMCG, tech, or financial services ...

level. Ability to write complex CTEs, window functions, and optimize joins for distributed systems. Experience with Marketing Mix Models (MMM). Understanding of Bayesian inference, Adstock transformations, and saturation curves. Useful experience Hands-on experience with at least one major DCR environment. Deep understanding of hypothesis testing ...

level. Ability to write complex CTEs, window functions, and optimize joins for distributed systems. Experience with Marketing Mix Models (MMM). Understanding of Bayesian inference, Adstock transformations, and saturation curves. Useful experience Hands-on experience with at least one major DCR environment. Deep understanding of hypothesis testing ...

level. Ability to write complex CTEs, window functions, and optimize joins for distributed systems. Experience with Marketing Mix Models (MMM). Understanding of Bayesian inference, Adstock transformations, and saturation curves. Useful experience Hands-on experience with at least one major DCR environment. Deep understanding of hypothesis testing ...

write complex CTEs, window functions and optimize joins for distributed systems. Proven experience building or managing Marketing Mix Models (MMM). Understanding of Bayesian inference, Adstock transformations, and saturation curves. Useful experience Hands-on experience with at least one major DCR environment. Deep understanding of hypothesis testing ...

write complex CTEs, window functions, and optimize joins for distributed systems. Proven experience building or managing Marketing Mix Models (MMM). Understanding of Bayesian inference, Adstock transformations, and saturation curves. Useful experience Hands-on experience with at least one major DCR environment. Deep understanding of hypothesis testing ...

write complex CTEs, window functions, and optimize joins for distributed systems. Proven experience building or managing Marketing Mix Models (MMM). Understanding of Bayesian inference, Adstock transformations, and saturation curves. Useful experience Hands-on experience with at least one major DCR environment. Deep understanding of hypothesis testing ...

write complex CTEs, window functions, and optimize joins for distributed systems. Proven experience building or managing Marketing Mix Models (MMM). Understanding of Bayesian inference, Adstock transformations, and saturation curves. Useful experience Hands-on experience with at least one major DCR environment. Deep understanding of hypothesis testing ...

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 ...

like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming (e.g., PyMC ) for uncertainty-aware predictions Stakeholder Collaboration : Demonstrated ability to work directly with stakeholders to scope, iterate ...

like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming (e.g., PyMC ) for uncertainty-aware predictions Stakeholder Collaboration : Demonstrated ability to work directly with stakeholders to scope, iterate ...

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 ...

metrics). Lead data discovery and exploratory data analysis; profile data quality, completeness, bias, lineage, and document data dictionaries/metadata. Apply rigorous statistical methods: experimental design (A/B and multivariate tests), hypothesis testing, power analysis, causal inference and quasi-experimental techniques. Engineer robust features and curated datasets … decisions in safety- and mission-critical contexts. Ensure Responsible Data and AI practices: explainability (e.g., SHAP/LIME), fairness/bias assessment, privacy-preserving methods, and alignment with MOD/regulatory and internal governance requirements. Build reproducible analysis artefacts (notebooks, scripts) and user-facing insights (dashboards, reports, briefings); automate ...

metrics). Lead data discovery and exploratory data analysis; profile data quality, completeness, bias, lineage, and document data dictionaries/metadata. Apply rigorous statistical methods: experimental design (A/B and multivariate tests), hypothesis testing, power analysis, causal inference and quasi-experimental techniques. Engineer robust features and curated datasets … decisions in safety- and mission-critical contexts. Ensure Responsible Data and AI practices: explainability (e.g., SHAP/LIME), fairness/bias assessment, privacy-preserving methods, and alignment with MOD/regulatory and internal governance requirements. Build reproducible analysis artefacts (notebooks, scripts) and user-facing insights (dashboards, reports, briefings); automate ...

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 … 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 ...

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 … 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 ...

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 … 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 ...

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 ...

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 ...

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 ...

clients, working closely with senior stakeholders to shape strategy and deliver measurable business outcomes. What You’ll Bring 🔥Deep knowledge of ML/statistical methods (e.g. supervised/unsupervised, Bayesian, time-series). ⚙️Strong Python skills with core libraries (NumPy, Pandas, Scikit-Learn) plus deep learning ...

clients, working closely with senior stakeholders to shape strategy and deliver measurable business outcomes. What You’ll Bring 🔥Deep knowledge of ML/statistical methods (e.g. supervised/unsupervised, Bayesian, time-series). ⚙️Strong Python skills with core libraries (NumPy, Pandas, Scikit-Learn) plus deep learning ...

environment. The role involves applying modelling, optimisation, and simulation techniques to improve operational efficiency and deliver production-ready solutions. Key Responsibilities Apply exploration-exploitation methods and optimisation techniques (surrogate models, Bayesian optimisation, imitation learning). Build dynamic feedback control models and stochastic simulation models. Develop and ...

environment. The role involves applying modelling, optimisation, and simulation techniques to improve operational efficiency and deliver production-ready solutions. Key Responsibilities Apply exploration-exploitation methods and optimisation techniques (surrogate models, Bayesian optimisation, imitation learning). Build dynamic feedback control models and stochastic simulation models. Develop and ...

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 … 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 ...