4 Decision Tree Jobs

well as models Model training with batch and real-time prediction scenarios: Use machine learning and statistical modeling techniques such as Reinforcement Learning,Decision Trees, Logistic Regression, Bayesian Analysis, Neural Networks and others to develop and evaluate algorithms to improve product/system performance, quality and accuracy Low more »

ethical use of AI, ensuring compliance with internal policies and external regulations. Deep understanding of traditional AI techniques: regression, classification, forecasting, clustering (e.g., Decision Trees, XGBoost, ARIMA, etc.) Strong understanding of programmatic LLM risk controls: output format validation, output context validation, content moderation etc. There is a lot more »

driven business transformation journey Develop tools for monitoring and analysing model performance and data precision. Present model findings and offer recommendations to key decision-makers and stakeholders The candidate: MSc/PhD in Data Science, Computer Science, Financial Engineering, Statistics, or related fields. 5+ years of industry experience … including distributions, statistical testing, and regression. Skilled in employing advanced machine learning algorithms and statistical techniques like regression, simulation, scenario analysis, modelling, clustering, decision trees, and neural networks to address business challenges. Demonstrated track record of applying statistical modelling and machine learning in industrial settings. Experience mentoring junior more »

and leverage new and existing data sources; capturing and explaining trends with innovative data features Clearly communicate results and proposed actions to key decision makers across the business Champion and facilitate automation of reporting, data pipelines and quality assurance Manage, coach and mentor team members, driving a culture … and issues in motor or home pricing Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering. Knowledge of the technical differences between different packages for some of these model types would be an more »