76 to 100 of 278 scikit-learn Jobs in the UK

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 ...

causal inference techniques (e.g., diff-in-diff, IV, matching) where randomization is impracticalFluency 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 ...

lifecycleexpertise: feature engineering, model training,evaluationand production deployment, includingMLOps, monitoring and drift detection. Practical knowledge of ML frameworks (e.g. scikit-learn,PyTorch,XGBoost) and cloud-native ML services (SageMaker, Azure ML, Vertex AI). Software Engineering: Production-grade Python services (FastAPI, AWS Lambda, event-driven patterns) and front ...

approaches, experimental design, and emerging AI/ML methodologies. Expert‐level Python proficiency with extensive experience using scientific and ML libraries (e.g., pandas, scikit‐learn, statsmodels, PyTorch/TensorFlow). Extensive hands‐on experience with large‐scale analytical data warehouses (BigQuery or equivalent). Experience defining modeling strategies ...

advanced degree in Computer Science, Mathematics, Statistics or a similar quantitative disciplineAre proficient with Python, including open-source data libraries (e.g Pandas, Numpy, Scikit learn etc.)Have experience productionising machine learning models and/or AI solutionsAre an expert in one of predictive modelling, classification, regression, optimisation ...

MLOps. What You Bring ·Proven experience building and iterating on ML models in a commercial setting. ·Expert-level Python skills (pandas, NumPy, scikit-learn, etc.) and strong statistical grounding. ·Experience working within cloud or modern data environments (Microsoft Fabric, Azure, or Databricks). ·Clear, impactful communication skills ...

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 ...

from data pipeline to production deployment before a model earns trust at scale. This is a second-line position, reviewing methodologies built with scikit-learn, LightGBM, graph models, anomaly detection, and increasingly GenAI-based components. You'll also build your own tooling — agentic AI systems that read model ...

Proficiency in Python and/or R, including software development best practices (version control, testing, documentation).Experience with machine learning libraries such as scikit-learn, PyTorch, or Keras. Strong data visualization and exploratory data analysis skills. Ability to translate complex analytical concepts into clear, actionable insights. Strong collaboration ...

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 ...

experience with SQL for data processing and analytics. Strong programming skills in Python , with experience using data science libraries such as Pandas, Numpy, Scikit-learn, and Keras/PyTorch . Experience with Databricks and Spark for data manipulation and querying. Prior experience in the retail industry, with ...

science processes. Experience in translating customer requirements into technical requirements and development objectives. Python expertise covering standard data science libraries (NumPy, pandas, matplotlib, Scikit-learn, PyTorch, etc...), web frameworks (Flask or FastAPI) and visualisation (Dash, Plotly, & Streamlit). Proficient in SQL. Working with unstructured data Building customer ...

science processes. · Experience in translating customer requirements into technical requirements and development objectives. · Python expertise covering standard data science libraries (NumPy, pandas, matplotlib, Scikit-learn, PyTorch, etc...), web frameworks (Flask or FastAPI) and visualisation (Dash, Plotly, & Streamlit). · Proficient in SQL. · Working with unstructured data · Building customer ...

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 ...

/or C/C++ is a strong plus Extensive experience with numerical and data science libraries (e.g., NumPy, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow, or similar) Proven experience building or maintaining machine learning systems in a distributed computing environment Proficiency developing in a Linux environment with attention ...

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 ...

with R and/or C/C++ is a strong plusExtensive experience with numerical and data science libraries (e.g., NumPy, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow, or similar)Proven experience building or maintaining machine learning systems in a distributed computing environmentProficiency developing in a Linux environment with ...

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 ...

major programming language for AI development (e.g., Python, C++)Familiarity with relevant AI/ML frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, or KerasUnderstanding of data structures, algorithms, and good software engineering practicesSome hands-on experience with AI/ML projects through academic coursework, research, internships ...

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 ...

interpret results, and make decisions under uncertainty. Deep hands-on experience with modern ML/DL stacks (e.g., PyTorch and/or TensorFlow, scikit-learn, Hugging Face Transformers).Proven experience with distributed training and scalable model serving, using modern architectures, tools, and frameworks. Hands-on experience deploying ...

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 ...