Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and communication skills , with the ability to translate complex technical findings into actionable insights More ❯
City of London, London, United Kingdom Hybrid / WFH Options
Singular Recruitment
Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and communication skills , with the ability to translate complex technical findings into actionable insights More ❯
london, south east england, united kingdom Hybrid / WFH Options
Singular Recruitment
Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and communication skills , with the ability to translate complex technical findings into actionable insights More ❯
london (city of london), south east england, united kingdom Hybrid / WFH Options
Singular Recruitment
Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and communication skills , with the ability to translate complex technical findings into actionable insights More ❯
Central London, London, United Kingdom Hybrid / WFH Options
Singular Recruitment
foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression, classification, clustering, time-series forecasting). Practical experience with Keras or PyTorch is required. Full-Stack Deployment: Demonstrable experience taking models to production, including building and deploying APIs with FastAPI and using Vertex AI for ML workflows. Visualization & Communication: Ability More ❯
of appropriate procedures for information governance, especially when using patient data Qualifications Essential Expertise building statistical models and use of machine learning using Python libraries such as Scikit-learn, Keras, and TensorFlow frameworks Experience in natural language processing Experience with one or more data management tools (SQL etc.) Demonstrable use of programming in collaborative and reproducible analysis pipelines Experience using More ❯
skills, a quick learning ability, and enthusiasm for tackling complex challenges. You are proficient in Python, with experience using PySpark and ML libraries such as scikit-learn, TensorFlow, or Keras . You are familiar with big data technologies (e.g., Hadoop, Spark), cloud platforms (AWS, GCP), and can effectively communicate technical concepts to non-technical stakeholders. Accommodation requests If you need More ❯
Vertex AI, Azure AI Services). Experience with a major conversational AI platform (Google Dialogflow, Amazon Lex, Rasa, or similar). A solid understanding of core Python ML libraries (Keras, scikit-learn, Pandas) and deep learning frameworks (TensorFlow, PyTorch). Desirable (but not essential) experience: Working with tools/interfaces for AI applications e.g. MCP protocol. Training traditional ML and More ❯
Vertex AI, Azure AI Services). Experience with a major conversational AI platform (Google Dialogflow, Amazon Lex, Rasa, or similar). A solid understanding of core Python ML libraries (Keras, scikit-learn, Pandas) and deep learning frameworks (TensorFlow, PyTorch). Desirable (but not essential) experience: Working with tools/interfaces for AI applications e.g. MCP protocol. Training traditional ML and More ❯
