9 of 9 Random Forest Jobs in London

skills using tools like Tableau, Spotfire, Power BI etc. Expertise in predictive modelling, including both parametric (e.g. logit/probit) and non-parametric (e.g. random forest, neural net) techniques as well as wider ML techniques like clustering/random forest (desirable). Tech Stack: SQL, Python More ❯

skills using tools like Tableau, Spotfire, Power BI etc. Expertise in predictive modelling, including both parametric (e.g. logit/probit) and non-parametric (e.g. random forest, neural net) techniques as well as wider ML techniques like clustering/random forest (desirable). Tech Stack: SQL, Python More ❯

skills using tools like Tableau, Spotfire, Power BI etc. Expertise in predictive modelling, including both parametric (e.g. logit/probit) and non-parametric (e.g. random forest, neural net) techniques as well as wider ML techniques like clustering/random forest (desirable). Tech Stack: SQL, Python More ❯

add or enhance data sets that deliver incremental value to New Look. Advanced Analytics: Experience in delivering and measuring data science projects such as random forest, k-means, linear regression. Optimization: Collaborate with teams to identify process optimization opportunities. Collaborate: Lead an analytical principle and deliver an analytics … analysts Proven experience leading analytics projects from conception to implementation, with strong project planning and management skills Strong understanding of analytical modelling techniques (e.g., random forest, k-means, linear regression) Excellent communication and presentation skills Accurate and relevant analytical insights Focus on Data Quality Improvement Promote Adoption Rate More ❯

understanding of computer science fundamentals, including data structures, algorithms, data modelling, and software architecture Solid understanding of classical Machine Learning algorithms (e.g., Logistic Regression, Random Forest, XGBoost, etc.), state-of-the-art research areas (e.g., NLP, Transfer Learning, etc.), and modern Deep Learning algorithms (e.g., BERT, LSTM, etc. More ❯

PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields. Expert in Python, R, SQL and a range of ML techniques (e.g., random forests, neural nets, reinforcement learning) Track record of delivering high-impact AI projects from concept to production Strong communication skills – able to translate complex More ❯

such as time to event analysis, machine learning, meta-analysis, mixed effect modeling, longitudinal modeling, Bayesian methods, variable selection methods (e.g., lasso, elastic net, random forest), design of clinical trials. Strong programming skills in R and Python. Demonstrated knowledge of data visualization, exploratory analysis, and predictive modeling. Excellent More ❯

commercial thinking Collaborating closely with marketing, BMD, and product teams to deliver analytics that support business priorities Building advanced models using techniques such as random forest , linear regression , and k-means clustering Translating analytical findings into clear, actionable recommendations for senior stakeholders Driving continuous improvement in data quality More ❯

commercial thinking Collaborating closely with marketing, BMD, and product teams to deliver analytics that support business priorities Building advanced models using techniques such as random forest , linear regression , and k-means clustering Translating analytical findings into clear, actionable recommendations for senior stakeholders Driving continuous improvement in data quality More ❯