1 to 25 of 30 Permanent Decision Tree Jobs in the UK

Testing Data Cleaning, Preprocessing, and Feature Engineering Data Visualization (e.g., Matplotlib, Seaborn, Plotly, Tableau) Machine Learning Fundamentals (e.g., Supervised, Unsupervised Learning) Machine Learning Algorithms (e.g., Regression, Classification, Clustering, Decision Trees, SVMs, Neural Networks) Model Evaluation and Validation Big Data Technologies (e.g., Spark, Hadoop - conceptual understanding) Database Querying (e.g., SQL) Cloud-based Data Platforms (e.g., AWS Sagemaker, Google AI More ❯

Testing Data Cleaning, Preprocessing, and Feature Engineering Data Visualization (e.g., Matplotlib, Seaborn, Plotly, Tableau) Machine Learning Fundamentals (e.g., Supervised, Unsupervised Learning) Machine Learning Algorithms (e.g., Regression, Classification, Clustering, Decision Trees, SVMs, Neural Networks) Model Evaluation and Validation Big Data Technologies (e.g., Spark, Hadoop - conceptual understanding) Database Querying (e.g., SQL) Cloud-based Data Platforms (e.g., AWS Sagemaker, Google AI More ❯

Testing Data Cleaning, Preprocessing, and Feature Engineering Data Visualization (e.g., Matplotlib, Seaborn, Plotly, Tableau) Machine Learning Fundamentals (e.g., Supervised, Unsupervised Learning) Machine Learning Algorithms (e.g., Regression, Classification, Clustering, Decision Trees, SVMs, Neural Networks) Model Evaluation and Validation Big Data Technologies (e.g., Spark, Hadoop - conceptual understanding) Database Querying (e.g., SQL) Cloud-based Data Platforms (e.g., AWS Sagemaker, Google AI More ❯

proactively contributing to the design, development, testing, and deployment of data science and AI solutions Experience and understanding of applied machine learning techniques in Python (e.g., xgboost, regression, decision trees) Experience with physics modelling highly desirable Practical knowledge and experience of developing AI solutions using advanced machine learning techniques (e.g., reinforcement learning, deep learning) Experience of working collaboratively More ❯

proactively contributing to the design, development, testing, and deployment of data science and AI solutions Experience and understanding of applied machine learning techniques in Python (e.g. xgboost, regression, decision trees) Experience with computational simulation/modelling highly desirable Practical knowledge and experience of developing AI solutions using advanced machine learning techniques (e.g. reinforcement learning, deep learning) Experience of More ❯

/enhancing search and information retrieval systems Exposure/experience in containerization technologies like docker, Kubernetes, AWS EKS etc. Proficiency in ML algorithms, such as multi-class classification, decision trees, support vector machines, and neural networks (deep learning experience strongly preferred) Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services e.g., AWS Bedrock, S3, SageMaker; Azure More ❯

. Microsoft suite - Excel, Powerpoint etc. Languages: Python, SQL, Git. Working towards more complex modelling of the data using innovative methods. Knowledge of Machine Learning: Classification (Random Forest, Decision Trees, KNN), Regression. Modelling (linear, sparse, logistic), Principal Component Analysis (PCA, PCR), clustering (K-means). Profile: Strong analytical skills, ability to generate strong insights and build convincing stories. More ❯

and ADX. Other services require a good working knowledge of Databricks, Logic Apps, and the Power Platform knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc) and their real-world advantages/drawbacks knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc More ❯

analysis, and reject analysis. Develop extensive knowledge of data structures, applications, and permissible uses across consumer, commercial, and open banking sectors. Apply statistical techniques (e.g., regression, machine learning, decision trees, CHAID analysis, and cluster analysis) to address business challenges. Utilise data mining tools and programming languages such as SAS, SQL, and Python to prepare data, perform analyses, and More ❯

analysis, and reject analysis. Develop extensive knowledge of data structures, applications, and permissible uses across consumer, commercial, and open banking sectors. Apply statistical techniques (e.g., regression, machine learning, decision trees, CHAID analysis, and cluster analysis) to address business challenges. Utilise data mining tools and programming languages such as SAS, SQL, and Python to prepare data, perform analyses, and More ❯

analysis, and reject analysis. Develop extensive knowledge of data structures, applications, and permissible uses across consumer, commercial, and open banking sectors. Apply statistical techniques (e.g., regression, machine learning, decision trees, CHAID analysis, and cluster analysis) to address business challenges. Utilise data mining tools and programming languages such as SAS, SQL, and Python to prepare data, perform analyses, and More ❯

analysis, and reject analysis. Develop extensive knowledge of data structures, applications, and permissible uses across consumer, commercial, and open banking sectors. Apply statistical techniques (e.g., regression, machine learning, decision trees, CHAID analysis, and cluster analysis) to address business challenges. Utilise data mining tools and programming languages such as SAS, SQL, and Python to prepare data, perform analyses, and More ❯

analysis, and reject analysis. Develop extensive knowledge of data structures, applications, and permissible uses across consumer, commercial, and open banking sectors. Apply statistical techniques (e.g., regression, machine learning, decision trees, CHAID analysis, and cluster analysis) to address business challenges. Utilise data mining tools and programming languages such as SAS, SQL, and Python to prepare data, perform analyses, and More ❯

products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams More ❯

products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams More ❯

products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams More ❯

Our Data teams are excited about the value of data within the business, powers our product decisions to improve things for our customers and enhance effective and agile decision making, regardless of what their primary tech stack may be. Hear from the team in our latest blogs or our case studies with Women in Tech . We are … think about fraud detection as a wider team Responsibilities: You will be part of a team that builds, evaluates and deploys machine learning models to improve and automate decision making Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions Design and maintain robust feature engineering pipelines for … related domain Experience working with large-scale, high-dimensional, and heavily imbalanced datasets Excellent skills in Python and SQL Solid understanding of classification algorithms such as gradient boosting decision trees, including pros and cons of different model architectures Strong feature engineering skills and experience in transforming raw data into useful model inputs Effective communication skills and able to More ❯

Our Data teams are excited about the value of data within the business, powers our product decisions to improve things for our customers and enhance effective and agile decision making, regardless of what their primary tech stack may be. Hear from the team in our latest blogs or our case studies with Women in Tech . We are … think about fraud detection as a wider team Responsibilities: You will be part of a team that builds, evaluates and deploys machine learning models to improve and automate decision making Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions Design and maintain robust feature engineering pipelines for … related domain Experience working with large-scale, high-dimensional, and heavily imbalanced datasets Excellent skills in Python and SQL Solid understanding of classification algorithms such as gradient boosting decision trees, including pros and cons of different model architectures Strong feature engineering skills and experience in transforming raw data into useful model inputs Effective communication skills and able to More ❯

Our Data teams are excited about the value of data within the business, powers our product decisions to improve things for our customers and enhance effective and agile decision making, regardless of what their primary tech stack may be. Hear from the team in our latest blogs or our case studies with Women in Tech . We are … think about fraud detection as a wider team Responsibilities: You will be part of a team that builds, evaluates and deploys machine learning models to improve and automate decision making Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions Design and maintain robust feature engineering pipelines for … related domain Experience working with large-scale, high-dimensional, and heavily imbalanced datasets Excellent skills in Python and SQL Solid understanding of classification algorithms such as gradient boosting decision trees, including pros and cons of different model architectures Strong feature engineering skills and experience in transforming raw data into useful model inputs Effective communication skills and able to More ❯

Responsibilities: Strategic Ownership : Define and drive the vision, roadmap and implementation of the orchestration stack, ensuring alignment with broader digital procurement strategy. Framework Design : Develop detailed orchestration frameworks, decision trees, and process flows, with a strong focus on user experience, policy alignment, and scalable deployment. Integration Leadership : Lead integration across intake-to-pay touchpoints (e.g. guided buying, sourcing More ❯

Responsibilities: Strategic Ownership : Define and drive the vision, roadmap and implementation of the orchestration stack, ensuring alignment with broader digital procurement strategy. Framework Design : Develop detailed orchestration frameworks, decision trees, and process flows, with a strong focus on user experience, policy alignment, and scalable deployment. Integration Leadership : Lead integration across intake-to-pay touchpoints (e.g. guided buying, sourcing More ❯

platforms or tools Log and manage system-related issues and enhancements, driving continuous improvement in technology usage Actively contribute to the refinement of ESCC SOPs, escalation workflows, and decision trees in response to evolving threat types and business requirements Risk, Compliance & Intelligence Integration Ensure GDPR, health & safety, and regulatory compliance across all ESCC data processing, surveillance, and incident More ❯

shape the brands of tomorrow by better understanding people everywhere. About the job As a Senior Data Scientist, you will play a pivotal role in driving data-driven decision-making and shaping strategic initiatives. Your expertise will directly impact the organisation's ability to understand client behaviour, refine predictive models, and deliver actionable insights that influence key business … control. Strong SQL skills and familiarity with databases like Redshift, Postgres, or Microsoft SQL Server. Solid understanding of machine learning algorithms, concepts, and applications, including regression, K-means, decision trees, neural networks, as well as exposure to generative AI and large language models (LLMs). Hands-on experience with cloud platforms such as AWS or Azure. We're … shape the brands of tomorrow by better understanding people everywhere. About the job As a Senior Data Scientist, you will play a pivotal role in driving data-driven decision-making and shaping strategic initiatives. Your expertise will directly impact the organisation's ability to understand client behaviour, refine predictive models, and deliver actionable insights that influence key business More ❯

deep knowledge of standardizing methods and machinery at the development stage to de-skill and streamline production. You’ll help translate this logic into standardized digital templates and decision trees. Capacity Planning Support (Real-world expertise essential) Use your understanding of chassis development, machine layout planning, and manpower allocation to guide how our tool models capacity and seasonality. More ❯

data analytics and insights initiatives. Reporting to the Head of FP&A - Systems & Controls, you’ll promote a data-driven culture and provide strategic insights to inform key decision-making at the executive level. You’ll define and lead FP&A’s MI strategy, embed advanced analytics and data science into performance reporting, and act as a strategic … and embrace change as an opportunity to grow. Technical skills required: Extensive experience in data management, MI analysis, and insights, with application of statistical methods to support strategic decision making, this doesn’t have to be from a Finance background. Experience working with machine learning techniques (e.g., clustering, decision trees, neural networks). Experience using programming More ❯