1 to 25 of 93 scikit-learn Jobs in the UK

years) as a Machine Learning Engineer , Data Scientist , or similar role. Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools ...

Skills AI/Technical Strong experience building and deploying machine learning and AI solutions in production. Hands‐on experience with: Python (PyTorch, TensorFlow, scikit‐learn) Data engineering tools (SQL, Spark, Airflow or similar) LLMs, NLP, and document intelligence (e.g. RAG, embeddings) Experience with cloud platforms (AWS, Azure ...

between data and lived football judgement Essential Requirements Technical Skills Advanced proficiency in Python and the data science stack (pandas/polars, scikit-learn, NumPy, matplotlib/plotly) Strong SQL skills ability to design schemas, write complex queries, and manage relational data across large datasets Demonstrated experience integrating ...

stack products Strong backend (Node.js, Python/Flask, FastAPI) and frontend (React, Next.js, Vue) fundamentals ML/data science proficiency: Python, SQL, pandas, scikit-learn, PyTorch/TensorFlow Experience with cloud platforms (AWS, GCP, Azure) and containerisation (Docker, Kubernetes) Proven ability to build data-secure, privacy-compliant infrastructure ...

Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience ...

learning technologies and best practices Skills and Experience • Strong programming skills in Python • Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn • Experience working with SQL and large datasets • Familiarity with data pipelines, feature engineering, and model optimisation • Understanding of MLOps practices, model deployment ...

consulting incl software development with a strong track record of delivering business value Proficiency in Python and ML/DL frameworks (e.g., scikit-learn, PyTorch, TensorFlow) Experience with AI/ML tools (e.g., Jupyter, MLflow, Vertex AI, Azure ML, Amazon SageMaker Experience of creating delivery client-facing proof ...

consulting incl software development with a strong track record of delivering business value Proficiency in Python and ML/DL frameworks (e.g., scikit-learn, PyTorch, TensorFlow) Experience with AI/ML tools (e.g., Jupyter, MLflow, Vertex AI, Azure ML, Amazon SageMaker Experience of creating delivery client-facing proof ...

GenAI: Experience with LLM APIs and Context Engineering (constructing prompts, managing context windows, evaluating behaviour). Engineering & Stack: Python: Expert level (Pandas, NumPy, Scikit-Learn). Data Engineering: Strong SQL skills and experience building data pipelines. Experience: Education: Degree in a quantitative field (Statistics, Mathematics, Computer Science, etc. ...

Tableau or Power BI. Published work, patents or conference presentations related to AI or data science in finance. Technical Skills Programming: Python (pandas, scikit‐learn, TensorFlow/PyTorch), R, SQL, Jupyter notebooks and version control (Git). Machine Learning: regression, classification, clustering, tree‐based models, neural networks, MLOps ...

Python and its core data science libraries: Pandas, NumPy, and SciPy . Machine Learning: Deep, practical experience with popular ML frameworks and libraries: scikit-learn, TensorFlow, or PyTorch . Statistics & Math: Strong foundation in statistical modeling , probability, hypothesis testing, regression analysis, and multivariate calculus/linear algebra ...

databases, visualization tools). Published research, patents, or conference presentations in AI or data science related to finance. Technical Skills Programming: Python (pandas, scikit‐learn, TensorFlow/PyTorch), R, SQL, notebooks, Git. Machine Learning: regression, classification, clustering, tree‐based models, neural networks; MLOps, model deployment, automated testing. Data ...

classical CV algorithms (edge detection, thresholding, color spaces). Data Analytics Fluency: Experience working with standard data manipulation libraries (NumPy, pandas, scikit-learn, SciPy). Communication: Advanced English proficiency to collaborate effectively in a global environment. Bonus Points (Nice to Have) Hands-on experience with Vision Transformers (ViTs ...

experience as a Machine Learning Engineer or equivalent role Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with cloud-based ML deployment (e.g., AWS SageMaker, Lambda, S3) Knowledge of MLOps/LLMOps tooling (e.g. ...

experience delivering advanced AI/ML solutions in industry or engineering environments. Strong expertise in Python and AI/ML libraries: PyTorch, TensorFlow, Scikit‐Learn, Keras, NumPy, Pandas, JAX, XGBoost, PyTorch Geometric, OpenCV, Transformers, LangChain, Pinecone . Proven hands‐on experience deploying models in production and building scalable ...

modeling approaches for each. Strong proficiency in Python and SQL, with hands‐on experience using major ML libraries/frameworks (e.g., PyTorch, TensorFlow, scikit‐learn) for model development and evaluation. Deep understanding of machine learning algorithms, model evaluation techniques (e.g., AUC, lift, calibration, stability), and data pipeline development ...

Engineer delivering predictive models into production environments, ideally for operational, supply chain, or critical infrastructure use cases. · Programming: Expert-level Python programming (pandas, scikit-learn, statsmodels, PyTorch/TensorFlow). · Platform Expertise: Deep, hands-on experience with Databricks and the AWS cloud ecosystem. · Mathematical Foundation: Strong understanding ...

understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining ...

Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers). Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain, LangGraph. Proven ...

operational teams to deliver features Skills & Experience: Strong Python and SQL skills Familiarity with Azure or AWS Some exposure to ML frameworks (e.g. scikit-learn, TensorFlow, or PyTorch) Background in data engineering, analytics engineering, or similar Desirables: ETL/ELT pipeline experience Microsoft Fabric/Data Lake knowledge ...

modern deep learning frameworks (e.g., PyTorch, TensorFlow), fine tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), and advanced ML libraries (e.g., scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Active contribution to open-source AI projects, research ...

SparkSQL in data or ML-focused roles. Strong understanding of machine learning concepts and experience using common ML libraries such as scikit‐learn, TensorFlow or PyTorch, alongside packages such as NumPy and Pandas. Knowledge of natural language processing techniques and API integration patterns for ML services. Experience delivering ...

REST & GraphQL APIs Cloud & Infra: AWS (ECS, S3, Lambda), Docker, Cloudformation, Pulumi, CI/CD with GitHub Actions ML/AI: PyTorch, TensorFlow, scikit‐learn, MLflow for experiment tracking, Zenml for ML pipelines Data: PostgreSQL, DynamoDB, data pipelines with Zenml (We’re open to evolving the stack ...

optimize queries using SQL. Familiarity with data manipulation libraries (Pandas, NumPy), Understanding of statistics and probability. Hands-on experience with ML libraries like Scikit-learn, TensorFlow, or PyTorch. Preferred Skills: Hands on experience in coding (mandatory python and SQL or C++). Understanding of Generative AI, Computer Vision ...

field Strong expertise in Large Language Models and advanced fine-tuning techniques Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn Experience with Generative AI tools like LangChain, Weaviate, LangGraph, or LlamaIndex Advanced programming skills in Python Competitive programming or data science background (e.g. ...