12 of 12 Remote/Hybrid scikit-learn Jobs in London

Conversational AI development Model training, testing and evaluation Prompt Engineering and AI workflow optimisation Programming & Frameworks Strong Python development skills PyTorch TensorFlow Scikit-Learn LangChain LangGraph Hugging Face FastAPI REST APIs Data Technologies SQL NoSQL Databases Data Modelling ETL Development Data Pipeline Engineering Vector Databases such as Pinecone ...

mentor engineers and scientists, lead applied research initiatives What You'll Bring Technical Expertise: Strong Python skills with the ML stack: NumPy, pandas, scikit-learn Hands-on experience with at least one deep learning framework (PyTorch, TensorFlow, JAX) Solid grounding in core ML—supervised, unsupervised, evaluation, regularisation, statistics ...

unstructured data, especially large-scale text or content datasets. Familiarity with common data science and machine learning tools such as Pandas, NumPy, SciPy, Scikit-learn, PyTorch, TensorFlow, or Matplotlib. The ability to translate complex and ambiguous requirements into practical, measurable, data-driven solutions, with strong analytical thinking, problem ...

leading ML/AI technical initiatives across multiple teams Strong experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality management ...

learning Exposure to machine learning models and corresponding statistics like K‐means, Bayesian, Clustering Strong technical skills with Python along with NumPy, Pandas, Scikit‐Learn Machine learning experience -> predictive and prescriptive modelling Data wrangling and data cleansing experience Strong analytical skills Any experience with Node.JS would be beneficial. ...

Solid understanding of Scrum practices and a strong Agile mindset. Advanced proficiency in Python and its key data and ML libraries (NumPy, PySpark, Scikit learn, TensorFlow/PyTorch) Working knowledge of generative AI models (e.g., ChatGPT, Claude), Databricks GenAI tooling (including embedding models), and modern data structures such ...

product teams to transform raw data into robust, auditable, and commercially valuable solutions. Skills & Experience Technical Expertise Strong proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL . Hands-on experience with Snowflake or similar cloud-based data warehouse platforms. Experience using Git and reproducible development practices. Strong ...

mathematical, ML and software techniques to solve industrial problems and deliver business impact. \n · Modern Tech Stack: Advanced proficiency in Python (pandas, NumPy, scikit-learn) and SQL. \n · Communication: Exceptional ability to explain complex technical concepts, algorithmic trade-offs, and probabilistic outputs to non-technical business partners. ...

Educated to bachelor’s degree level or equivalent qualification/relevant work experience Excellent programming skills, predominantly across the Python/Anaconda suite (Scikit-learn, Pandas, Numpy) Understanding financial markets, risk (e.g., Know Your Client, anomaly detection/Machine Learning, project management) Excellent interpersonal skills with the ability ...

drive Marquee platform adoption and ensure clients receive the most relevant, timely, and actionable content. You will utilize technologies including Python (Pandas, Polars, Scikit‐learn, TensorFlow/PyTorch), Jupyter, Trino, SQL, and gain exposure to graph database technologies. RESPONSIBILITIES Design, build, and maintain robust data pipelines for feature … model deployment and monitoring in a production environment. Exceptional programming skills in Python, with a command of data science libraries (e.g., Pandas, NumPy, Scikit‐learn). Experience with big data technologies (e.g., Spark, Trino, Hadoop) and ideally cloud platforms (e.g., AWS, GCP, Azure) for scalable data processing, storage ...

expertise: You have a general understanding of REST APIs (design, integration, authentication). You have experience building, tuning, or deploying ML models (e.g., scikit‐learn, XGBoost, PyTorch, TensorFlow) in production settings. Experience with AI use cases in financial services (e.g. fraud detection, credit scoring, underwriting) is a strong ...

awareness of modern approaches such as natural language processing and deep learning Strong Python skills and experience with common libraries such as Pandas, scikit-learn and Jupyter Experience working with SQL and data pipelines to prepare and transform data for model training Understanding of model evaluation, monitoring ...