1 to 25 of 156 scikit-learn Jobs in the UK excluding London

techniques, with hands-on experience in either academia or industry. Proficiency in Python and experience with ML/NLP libraries like TensorFlow, PyTorch, scikit-learn, or Hugging Face. Experience working with cloud platforms such as AWS, GCP, or Azure. Familiarity with advanced NLP methods, including Prompt Engineering, Parameter More ❯

like Flask, FastAPI, Pandas, PySpark, PyTorch, to name a few. Proficiency in statistics and/or machine learning libraries like NumPy, matplotlib, seaborn, scikit-learn, etc. Experience in building ETL/ELT processes and data pipelines with platforms like Airflow, Dagster, or Luigi. What's important for us More ❯

Strong programming skills in Python or R, with proficiency in data manipulation libraries (e.g., Pandas, NumPy). Experience with machine learning frameworks (e.g., Scikit-Learn, TensorFlow) and data visualization tools (e.g., Tableau, Matplotlib). Solid understanding of statistics, probability, and data-driven decision-making. Experience working with databases More ❯

modeling, and/or NLP. Proficiency in programming languages such as Python, R, or Julia, with experience using ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Familiarity with biological datasets such as genomic, transcriptomic, proteomic, or imaging data. Experience working with large-scale datasets and cloud computing platforms More ❯

techniques such as XGBoost, deep neural networks, and transformers Practical knowledge of ML libraries and frameworks such as Fastai, Keras, TensorFlow, PyTorch, and Scikit-learn Ability to research, understand, and apply emerging machine learning techniques Programming & Data Engineering Proficiency in programming languages such as Python (preferred) and C++ More ❯

techniques such as XGBoost, deep neural networks, and transformers Practical knowledge of ML libraries and frameworks such as Fastai, Keras, TensorFlow, PyTorch, and Scikit-learn Ability to research, understand, and apply emerging machine learning techniques Programming & Data Engineering Proficiency in programming languages such as Python (preferred) and C++ More ❯

techniques such as XGBoost, deep neural networks, and transformers Practical knowledge of ML libraries and frameworks such as Fastai, Keras, TensorFlow, PyTorch, and Scikit-learn Ability to research, understand, and apply emerging machine learning techniques Programming & Data Engineering Proficiency in programming languages such as Python (preferred) and C++ More ❯

research - Experience programming in Java, C++, Python or related language - 3+ years' experience with modeling languages and tools like PyTorch/TensorFlow, R, scikit-learn, numpy, scipy, etc - Solid ML background and familiar with standard NLU, NLG, and LLM techniques PREFERRED QUALIFICATIONS - PhD in Computer Sciences, Electrical Engineering More ❯

or similar Python frameworks like Streamlit) for dashboard creation. Experience with Machine Learning model development and data science workflows (including frameworks such as scikit-learn, PyTorch, or TensorFlow). Experience in Quantitative Finance or strong interest in mathematical/financial modeling, derivatives pricing, or algorithmic trading. Familiarity with More ❯

strategies across the Civil Service. Key Skills and Experience • Strong programming skills in Python, R, or SQL. • Experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch). • Proficiency in data manipulation and analysis (e.g., Pandas, NumPy, Spark). • Knowledge of data visualization tools (e.g., Power BI, Tableau More ❯

Strong academic background in Data Science, Machine Learning, AI, or a related field. Technical Skills – Proficiency in Python, SQL, ML frameworks (TensorFlow, PyTorch, scikit-learn), and at least one OOP language (Rust, C++, C#). AI & NLP Expertise – Hands-on experience with LLMs, NLP, and AI-driven data More ❯

or coursework in machine learning, deep learning, or AI techniques (e.g., supervised learning, neural networks, NLP). Proficiency in Python and libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Transformers. Familiarity with data preprocessing, model evaluation, and deploying models in real-world environments. A passion for AI More ❯

communication skills. Experience working with real-world data sets and building scalable models from big data. Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow. Experience with large-scale distributed systems. Our inclusive culture empowers Amazonians to deliver the best results for our customers. More ❯

learning models and algorithms in real-world applications. - Strong proficiency in Python programming and popular machine learning libraries/frameworks (eg, TensorFlow, PyTorch, scikit-learn). - Deep understanding of machine learning concepts and techniques, including supervised/unsupervised learning, deep learning, reinforcement learning, etc. - Strong communication and interpersonal More ❯

Proficiency in Python (preferred) and/or other relevant languages (e.g., R, Java, C++). Machine Learning & AI Frameworks: Experience with TensorFlow, PyTorch, Scikit-learn, or similar libraries. Data Manipulation & Analysis: Strong skills in Pandas, NumPy, and SQL for handling and analysing large datasets. Cloud Computing: Familiarity with More ❯

all domains: data pre-processing and post-processing, machine learning, deep learning, time-series algorithms, explainability methods and more, using Python packages (including Scikit-Learn, Pandas, NumPy, NLTK, etc.). Preferred skills and technical familiarity At least 4 years of proven experience in Data Science. Sc./M.Sc. More ❯

EC2, S3, Lambda, SageMaker, ECS) and cloud infrastructure management Programming and ML Frameworks: Proficiency in Python and experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch CI/CD Experience: Experience with CI/CD tools and practices (e.g., GitHub Actions, Jenkins) and the ability to More ❯

AWS SageMaker and Lambda, and you'll know your way around Git, SQL, and common Python data science libraries (like pandas/polars, scikit-learn, xgboost/lightGBM, and TensorFlow/PyTorch). Bonus points if you've worked with linear programming, or have experience in time series More ❯

algorithms applied to computer vision challenges Knowledgeable about key architectures like Vision Transformers, DeepLabv3, and SegFormer Proficient in Python and ML tools, including Scikit-Learn, NumPy, Pandas, PyTorch, TensorFlow, or Keras Capable of applying machine learning to solve real-world problems Please apply via the link for immediate More ❯

algorithms applied to computer vision challenges Knowledgeable about key architectures like Vision Transformers, DeepLabv3, and SegFormer Proficient in Python and ML tools, including Scikit-Learn, NumPy, Pandas, PyTorch, TensorFlow, or Keras Capable of applying machine learning to solve real-world problems Please apply via the link for immediate More ❯

machine learning and software engineering. Experience deploying machine learning models in production environments. Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn). Familiarity with cloud platforms like GCP, AWS, or Azure. Experience with CI/CD pipelines for machine learning (e.g., Vertex AI). More ❯

in Python. Significant experience with SQL (e.g., RDBMS, Spark, Presto, or BigQuery). Experience with machine learning, optimization, and data manipulation tools (e.g., scikit-learn, XGBoost, cvxpy, Pandas, Spark, or PyTorch). Experience with at least one low-level or scientific language (e.g., C, Rust, Go, Julia, or More ❯

science methods using both quantitative and qualitative metrics. Strong mathematical and statistical background. Deep knowledge of Python and data science packages such as Scikit learn, Keras, Tensor flow, and PySpark. Experience and understanding of mixed technical teams such as engineering, architects, business analysts. Familiar with MLOps industry best More ❯

science methods using both quantitative and qualitative metrics. Strong mathematical and statistical background. Deep knowledge of Python and data science packages such as Scikit learn, Keras, Tensor flow, and PySpark. Experience and understanding of mixed technical teams such as engineering, architects, business analysts. Familiar with MLOps industry best More ❯

languages. Experience in patents or publications at top-tier peer-reviewed conferences or journals. PREFERRED QUALIFICATIONS Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. Experience with large scale distributed systems such as Hadoop, Spark etc. Amazon is an equal opportunities More ❯