26 to 50 of 132 scikit-learn Jobs in London

mixed integer programming, heuristics) Fluent in Python (required) and other programming languages (preferred) with strong skills in applying DS, ML, and OR packages (scikit‐learn, pandas, numpy, gurobi, etc.) to solve real‐life problems and visualise the outcomes (e.g., seaborn) Proficient in working with cloud platforms (AWS preferred ...

happy to discuss further. Preferred Qualifications Experience with Vue or other similar JavaScript framework Experience with simple NLP methods using Gensim and scikit-learn Knowledge of testing methodologies and an uncompromising ethic around automated testing Experience with microservices architecture Perks Coming on board in the early stages ...

Experience with Cloud AI services such as Azure ML, AWS SageMaker, GCP Vertex AI. Hands-on experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch. Practical knowledge of algorithms and techniques such as regression, decision trees, random forest, XGBoost, k-means, anomaly detection, and time ...

end. Hands-On & Architectural Expertise: Strong software engineering foundations across the modern AI stack: Classic ML & Stats: Classical ML techniques (TensorFlow, PyTorch, scikit-learn), forecasting, and feature engineering. Generative AI & Agents: RAG, tool-calling, orchestration, guardrails, LLM-based agentic architectures, and fine‐tuning. Cloud & MLOps: Production deployment ...

predictive modelling, classification, regression, optimisation or recommendation systems Strong proficiency in Python and open-source data libraries such as Pandas, NumPy and Scikit-learn A solid grounding in statistical methodologies, along with data extraction, manipulation and feature engineering techniques Experience with Spark, agile delivery methods and CI/ ...

production and supporting them post-deployment. Strong Python programming skills, including object-oriented design and proficiency with key ML libraries (e.g., PyTorch, TensorFlow, Scikit-Learn). Solid understanding of probability and statistical modeling to support robust model development and interpretation. Experience with cloud platforms (especially Azure and/ ...

inference techniques (e.g., diff‐in‐diff, IV, matching) where randomization is impractical Fluency in Python and core data/ML libraries (pandas, NumPy, scikit‐learn, PyTorch or TensorFlow), combined with solid software engineering practices (clean code, testing, version control, code review) Proficient with large‐scale data: strong ...

partnership model, conveying information clearly and creating trust with stakeholders. Experience with machine learning frameworks (e.g., PyTorch, TensorFlow), data science packages (e.g., Scikit-Learn, NumPy, SciPy, Pandas, statsmodels) and GenAI toolkit Experience in ML Ops #J-18808-Ljbffr ...

executing marketing experiments Proficiency in applying ML techniques to marketing and customer datasets Strong proficiency in Python and data science libraries (pandas, NumPy, scikit-learn, statsmodels, or equivalent) Strong command of SQL for querying and analyzing large-scale marketing and media datasets Preferred Qualifications Experience with paid media ...

development life cycle processes and tools: CI/CD, version control (git), testing frameworks, MLOps. Experience with data science Python libraries such as Scikit-learn, Pandas, NumPy, Pytorch etc. Comfortable working with Docker and containerised applications Experience using AWS or similar cloud computing platform Experience delivering machine learning ...

that deliver measurable business impact Technical Mastery: High proficiency in Python and SQL. Expert-level experience with the Python data stack (pandas, NumPy, scikit-learn) and at least one major ML framework (such as PyTorch or XGBoost/LightGBM) Systemic Problem Solving: Ability to work on unique issues ...

solutions. You’re comfortable writing production-grade code, not just notebooks. Solid skills in Python and SQL, including standard libraries (Polars, Scipy, NumPy, Scikit-Learn). Experience building or maintaining data pipelines and tools that are reliable and maintainable. Clear communication skills: able to break down problems into ...

security expectations; experience coaching engineers on safe, compliant adoption. Good understanding of data structures, algorithms, and practical machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn). Proficiency in automation, continuous delivery (CI/CD), and cloud-native development (preferably AWS). Hands-on practical experience delivering system design ...

navigate large, messy warehouses (BigQuery, Snowflake, Redshift, or similar) and write performant, readable queries. Solid Python (or R) for analysis and modeling: pandas, scikit-learn, statsmodels, and at least one deep-learning or gradient-boosting framework (XGBoost, LightGBM, PyTorch, TensorFlow). Experimentation fluency. You understand the math behind ...

Knowledge of data structures, algorithms, machine learning, data mining, information retrieval, and statistics Understanding of machine learning frameworks: Tensorflow, Pytorch, pyG, Keras, MXNet, Scikit-Learn Strong programming knowledge of Python and Spark; proficiency in vector operations using numpy, scipy; experience with distributed computation using multithreading, multi GPUs, Dask ...

security expectations; experience coaching engineers on safe, compliant adoption. Good understanding of data structures, algorithms, and practical machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn). Proficiency in automation, continuous delivery (CI/CD), and cloud-native development (preferably AWS). Hands-on practical experience delivering system design ...

data science, machine learning, pricing analytics, or commercial operations. Strong technical background in Python or R, SQL, and applied ML libraries (e.g. scikit-learn, TensorFlow, XGBoost). Experience with data visualization tools (Tableau, Power BI, or similar). Understanding of statistical methods, supervised/unsupervised learning, and business ...

instinct for leakage, bias and overfitting in messy real-world data. Strong ML fundamentals across classical ML and deep learning (pandas, scikit-learn, XGBoost or LightGBM, PyTorch), and the judgement to tell when a language model is the wrong tool. A deep understanding of how modern models ...

around you. Requirements Essential Expert Python, with deep hands-on PyTorch experience (TensorFlow also welcome) and the surrounding ecosystem: Hugging Face Transformers, timm, scikit-learn, NumPy, pandas, OpenCV. Production experience on AWS, specifically Amazon SageMaker: training and processing jobs, pipelines, model registry, endpoints. Practical MLOps: experiment tracking ...

customer-facing products Experience in travel, transport, marketplaces, or similarly complex digital platforms Our technology stack Python and associated ML/DS libraries (scikit-learn, NumPy, LightGBM, Pandas, LangChain/LangGraph, TensorFlow, etc.) PySpark AWS cloud infrastructure: EMR, ECS, Athena, etc MLOps/DevOps: Terraform, Docker, Airflow, MLFlow ...

retraining, and monitoring for drift and model degradation (MLflow, SageMaker, Databricks ML, Vertex AI or comparable) Are comfortable with ML frameworks such as scikit-learn, PySpark MLlib, or PyTorch/TensorFlow, enough to productionise a data scientist’s work, reason about what a model needs from the data ...

around you. Requirements Essential Expert Python, with deep hands‐on PyTorch experience (TensorFlow also welcome) and the surrounding ecosystem: Hugging Face Transformers, timm, scikit‐learn, NumPy, pandas, OpenCV. Production experience on AWS, specifically Amazon SageMaker: training and processing jobs, pipelines, model registry, endpoints. Practical MLOps: experiment tracking ...

working with non‐technical stakeholders to scope, design and deliver effective ML solutions. Insert skills. Proficient with the Python data science stack (pandas, scikit‐learn, Jupyter, etc.) and version control tools like Git. Exposure to LLMOps, model monitoring, CI/CD and related technologies (Docker, MLflow, Kubernetes, FastAPI ...

interpretation. Proficiency in Object‐Oriented programming in Python with expertise in key data science and machine learning libraries (e.g. TensorFlow, PyTorch and Scikit‐Learn). Expertise in cloud technologies (emphasis on Azure and/or AWS) and deployment practices, ensuring seamless and scalable delivery. Proven ability to establish ...

appropriate. Experience designing evaluation frameworks for AI‐generated or retrieval‐based outputs. Data & Engineering Familiarity with machine learning frameworks such as PyTorch, TensorFlow, Scikit‐learn, and Hugging Face. Experience with cloud platforms and modern development workflows, including Git and CI/CD. Understanding of MLOps practices, including experiment ...