51 to 75 of 179 scikit-learn Jobs in the UK

star schemas and Kimball methodologies Experience supporting advanced Power BI models (DAX and Power Query) Exposure to ML/AI concepts (e.g. scikit-learn, TensorFlow) or an interest in preparing data for LLMs, RAG architectures or predictive models Experience with Docker and/or Terraform (desirable) What ...

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 ...

roles, not just in theory We're looking for: Strong hands-on AI/ML and Data Science expertise (Python essential — NumPy, Pandas, Scikit-learn; exposure to PyTorch, TensorFlow, LangGraph or similar a plus) Proven experience delivering technical training to a mix of technical and non-technical audiences ...

model prototyping to production deployment, integration, and ongoing monitoring. You are proficient in Python and its data/ML ecosystem (e.g. pandas, scikit-learn, PyTorch, TensorFlow), and you can apply statistical and machine learning techniques confidently in real-world settings. You have deployed models into live systems ...

efficiency.* Proficiency in the following version control language: Git* Proficiency in any of the following AI/ML frameworks: Huggingface, Torch, Tensforflow, Scikit-Learn, and Spacy* Experience in of any of the following additional platforms related to MLOps: MLFlow, dbt, Docker, Kubernetes.* Experience with working cloud environments such ...

MLOps and production deployment AI evaluation, testing and observability AI governance, model risk and engineering controls ML frameworks such as PyTorch, TensorFlow or Scikit-learn Experience operating in complex, regulated or high-risk environments would be particularly valuable. More important than any individual technology is the ability ...

experience in translating technical methods to non-technical stakeholders Strong programming experience in Python and the relevant analytics libraries (e.g., pandas, numpy, matplotlib, scikit-learn, statsmodels, pymc, pytorch/tf/keras, langchain). R and C++ optional. Experience with version control (GitHub) ML experience with causality, Bayesian ...

data and implementing data science processes. Experience in translating customer requirements intotechnical requirements and development objectives. Pythonexpertisecovering standard data sciencelibraries (NumPy, pandas, matplotlib, Scikit-learn,PyTorch, etc),web frameworks (Flask or FastAPI) and visualisation(Dash,Plotly,&Streamlit). Proficient inSQL. Working with unstructured data Building customer and stakeholder ...

data and implementing data science processes. Experience in translating customer requirements intotechnical requirements and development objectives. Pythonexpertisecovering standard data sciencelibraries (NumPy, pandas, matplotlib, Scikit-learn,PyTorch, etc),web frameworks (Flask or FastAPI) and visualisation(Dash,Plotly,&Streamlit). Proficient inSQL. Working with unstructured data Building customer and stakeholder ...

stakeholders. Who we’re looking for: You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch. You possess strong Python skills and solid experience in software engineering best practices. You bring hands‐on experience with cloud platforms ...

stakeholders. Who we're looking for: You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch. You possess strong Python skills and solid experience in software engineering best practices. You bring hands-on experience with cloud platforms ...

with significant industry or research experience in the field Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit‐Learn, Pandas) Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals ...

deep technical expertise in particular topics and broad knowledge for solving complex problems; Have strong Python skills and practical experience operationalising models with Scikit-learn, TensorFlow, or PyTorch; Be an expert in at least one major Cloud Solution Provider, such as Azure, GCP, or AWS; Have experience leading ...

software engineering best practices. Experience across the machine learning lifecycle, including taking models into production. Hands-on experience with frameworks such as Scikit-learn, TensorFlow or PyTorch. Experience working with cloud platforms such as AWS, Azure or GCP. Knowledge of cloud architecture, infrastructure and security. Practical experience with ...

would be an advantage: LLMs AI Agents Graph analytics Behavioural modelling Cyber security Network intelligence PyTorch XGBoost Our technology Python SQL AWS PyTorch Scikit-learn XGBoost Docker Kubernetes Claude Code GitHub Copilot LLMs AI Agents Why Friend MTS? AI is becoming one of the core capabilities of Friend ...

experience The successful candidate will have: Three or more years of commercial Data Science or applied analytics experience. Strong Python skills, including pandas, scikit-learn and common Data Science libraries. Advanced SQL skills and experience working with large or varied datasets. Commercial experience using Snowflake. A good grounding ...

modern machine learning — able to understand, integrate, and extend the functionality of an ML library (NumPy, SciPy, Pandas, and frameworks such as scikit-learn or PyTorch) Understanding of core ML concepts — model training, evaluation, and production trade-offs — enough to design robust interfaces around them Experience with DevOps ...

modern machine learning — able to understand, integrate, and extend the functionality of an ML library (NumPy, SciPy, Pandas, and frameworks such as scikit-learn or PyTorch) Understanding of core ML concepts — model training, evaluation, and production trade-offs — enough to design robust interfaces around them Experience with DevOps ...

modern machine learning — able to understand, integrate, and extend the functionality of an ML library (NumPy, SciPy, Pandas, and frameworks such as scikit-learn or PyTorch) Understanding of core ML concepts — model training, evaluation, and production trade-offs — enough to design robust interfaces around them Experience with DevOps ...

operating models on Databricks. Familiarity with cloud‐based application development (AWS & Azure). Familiarity with one or more ML frameworks and technologies: scikit‐learn, xgboost, TensorFlow, PyTorch, Spark, SageMaker, Vertex AI, Kubeflow, Seldon, Triton. Strong communication skills, able to express ideas clearly and collaborate across teams. #J ...

modern Deep Learning algorithms (e.g. BERT, LSTM, etc.). Strong knowledge of SQL and Python’s ecosystem for data analysis (Jupyter, Pandas, Scikit‐Learn, Matplotlib). Strong software development skills (Python is the preferred language). Strong management and leadership skills – previous experience managing a team. Strong influencing ...

etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) Strong knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib) Strong software development skills (Python is the preferred language) Proven experience in deploying ML/AI services suing Kubernetes & KubeFlow Strong management ...

etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) Strong knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib) Strong software development skills (Python is the preferred language) Proven experience in deploying ML/AI services suing Kubernetes & KubeFlow Strong management ...

online) Solid understanding of statistical methods, including GLMs and modern ML techniques Proven ability to build and deploy production-quality Python applications (pandas, scikit-learn) Experience with DevOps and ML tooling, including Kubernetes, Docker, CI/CD, and git-based workflows Familiarity with cloud platforms (AWS) and cloud ...

evolving stakeholder needs into features, and drive delivery. Strong Python for data and backend work - Pandas plus optimization/scientific libraries (e.g. Pyomo, Scikit-Learn) Building simulation, forecasting, and KPI/analytics frameworks to model financial or operational outcomes Data engineering: ingestion and transformation pipelines for time-series ...