24 of 24 Remote/Hybrid scikit-learn Jobs in England

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 ...

date with the latest advancements in machine learning and AI technologies Required Skills & Experience Strong programming skills in Python (e.g., TensorFlow, PyTorch, Scikit-learn) Experience deploying ML models using cloud platforms (AWS, Azure, or GCP) Solid understanding of machine learning algorithms, data structures, and software engineering principles Experience ...

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 ...

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 ...

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 ...

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. ...

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 ...

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 ...

Scientist with production ML exposure Strong understanding of ML algorithms, model development, and deployment Experience with Python and ML frameworks (e.g. TensorFlow, PyTorch, scikit-learn) Familiarity with data pipelines and cloud or on-prem environments Understanding of MLOps principles Ability to work in secure or regulated environments Eligibility ...

products Deep GenAI and classical ML expertise Hands-on experience with Agentic AI, evaluation frameworks, RAG and prompt engineering Strong Python skills (PyTorch, scikit-learn, modern ML frameworks) A commercial mindset, balancing tech investment with customer value The credibility to lead technically and influence at exec level Desirable ...

independently and take ownership of complex problems Strong communication skills, with the ability to explain technical concepts clearly Technical Environment Python (e.g. pandas, scikit-learn, TensorFlow/PyTorch where relevant) SQL and large-scale data processing Cloud-based environments (e.g. AWS, Azure, or similar) Experience with model deployment ...

measurable impact Experience taking models into production and managing performance over time Prior experience leading or mentoring Data Scientists Strong Python (pandas, numpy, scikit-learn or similar) Strong SQL (complex joins, aggregations, analytical functions) Solid grounding in applied statistics, evaluation design, calibration, bias/fairness Experience working closely ...

including, University degree (STEM or quantitative discipline) Strong foundations in mathematics and analytical reasoning Strong hands-on experience with, programming & Analytics: Python, SQL, Scikit-learn, TensorFlow Data & Cloud: AWS (Athena, S3, Redshift), data warehousing, ETL pipelines Visualisation & Tools: Jupyter, Visual Studio Code, Microsoft Excel, dashboards and reporting solutions ...

including, University degree (STEM or quantitative discipline) Strong foundations in mathematics and analytical reasoning Strong hands-on experience with, programming & Analytics: Python, SQL, Scikit-learn, TensorFlow Data & Cloud: AWS (Athena, S3, Redshift), data warehousing, ETL pipelines Visualisation & Tools: Jupyter, Visual Studio Code, Microsoft Excel, dashboards and reporting solutions ...

equivalent role Strong expertise in AI, machine learning, and statistical methods Proficiency in Python and ML/data analysis libraries (e.g., pandas, numpy, scikit-learn, PyTorch, transformers, statsmodels) Experience with cloud-based ML deployment (e.g., AWS services) Ability to absorb complex scientific concepts and apply them to real ...

environments. We're looking for individuals with: Experience: Proven background as a Machine Learning Engineer. Technical Skills: Strong in SQL and Python (Pandas, Scikit-learn, Jupyter, Matplotlib). Data transformation & manipulation : experience with Airflow, DBT and Kubeflow Cloud: Experience with GCP and Vertex AI (developing ML services). ...

development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training ...

degree or higher in a STEM subject (or equivalent portfolio/work experience). You must have familiarity with ML frameworks such as scikit-learn, PyTorch and a strong grasp of statistical inference, hypothesis testing and experimental design. In your career so far, you will have ideally gained ...

This is a unique opportunity to work at the cutting edge of AI, data technology, and elite football analytics. As a Data Scientist, you’ll join a collaborative, high-performing team with a culture rooted ...

problem-solving skills: Able to decompose messy, real-world problems and craft tailored solutions. Proficient in Python & data science: pandas/Polars, NumPy, scikit-learn, Jupyter, Plotly (or similar) Confident with data cleaning, analysis, transformation, and visualisation. Excellent communication: Advanced written and spoken English; concise, direct, and audience … Postgres. TypeScript fluency: Able to read TS and collaborate on data contracts with the Command team. Our environment Python, Polars/pandas, NumPy, scikit-learn, Plotly, SQL/Postgres, NVIDIA cuOpt, HERE APIs, AWS (S3, ECS/Lambda, SNS/SQS), Docker, GitHub Actions, TypeScript/Node (Command ...

Computer Vision Research Engineer About iProov iProov provides science-based biometric solutions that enable the world’s most security-conscious organizations to streamline secure remote onboarding and authentication for digital and physical access. Our award ...