4 of 4 Random Forest Jobs in London

AI (developing ML services). Expertise: Solid understanding of computer science fundamentals and time-series forecasting. Machine Learning: Strong grasp of ML and deep learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, BERT, LSTM, NLP, Transfer Learning). Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community we More ❯

machine learning services) Timeseries forecasting Solid understanding of computer science fundamentals, including data structures, algorithms, data modelling and software architecture Strong knowledge of Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) as well as state-of-the-art research area (e.g. NLP, Transfer Learning etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) Machine Learning More ❯

computer science, mathematics, engineering, science, economics or finance). A good understanding of statistical modelling knowledge or any machine learning technique knowledge (such as hypothesis testing, regression, logistic regression, random forest, etc.) Good stakeholder management experience. Comfortable presenting to senior leadership and C-suite. Experience in conducting A/B testing experimentation Strong experience in finding data insights More ❯

Spring & Spring Boot, Java, Python, FastAPI Frontend: Vue.js Cloud: AWS Databases: Elasticsearch & Postgres And more... This role offers exciting opportunities to dive into various areas, including Natural Language Processing, Random Forest and Monte Carlo Simulations, Classification, Big Data ETL Pipelines, High Volume Event Processing, Predictive Analysis, CI/CD Cloud Ops, Mentoring, UX Design, Data Visualization, and Build More ❯