26 to 50 of 940 scikit-learn Jobs in the UK

Good working knowledge of Python Implementing end-to-end ML pipelines Hand-on experience in Python data science ecosystem (e.g. numpy, scipy, pandas, scikit-learn, matplotlib etc.) Deep Learning frameworks (TensorFlow, PyTorch, MLX) Popular classification and regression techniques Unsupervised learning & matrix factorisation algorithms Natural Language Processing (NLP) and More ❯

techniques, including LLMs, GenAI, and automated AI systems. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and data science libraries (e.g., NumPy, pandas, scikit-learn). Proficiency in Python, R, or other relevant programming languages. Proficiency in working with large datasets, data wrangling, and data preprocessing. Experience in More ❯

experience Proven track record of delivering AI solutions for complex scientific problems Experience with machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn, spaCY), and data processing techniques. Demonstrated experience in developing and deploying machine learning models in production environments. Experience with AI Cloud Platforms (AWS More ❯

are searching for are: style="margin-bottom:0.0in;margin-top:0.0px;text-align:justify"- -Programming Skills: Proficiency in Python, data analytics, deep learning (Scikit-learn, Pandas, PyTorch, Jupyter, pipelines), and practical knowledge of data tools like Databricks, Ray, Vector Databases, Kubernetes, and workflow scheduling tools such as Apache More ❯

their potential application within our business. About you: DATA SCIENCE • Extensive proficiency in Python and its associated data science libraries (e.g., Pandas, NumPy, scikit-learn, TensorFlow, PyTorch) and data visualisation libraries (e.g., Plotly, Dash). • Strong knowledge and practical application of statistical analysis and data visualization techniques. • Strong More ❯

AI/ML toolkit Support business-development by shaping analytics in proposals and thought-leadership Tech you'll use (and learn) Python SQL scikitlearn XGBoost TensorFlow/PyTorch LangChain Airflow dbt AWS/GCP/Azure Docker Kubernetes Tableau Streamlit GitHub Actions We're tech agnostic and believe in More ❯

AI/ML toolkit Support business-development by shaping analytics in proposals and thought-leadership Tech you’ll use (and learn) Python SQL scikitlearn XGBoost TensorFlow/PyTorch LangChain Airflow dbt AWS/GCP/Azure Docker Kubernetes Tableau Streamlit GitHub Actions We’re tech agnostic and believe in More ❯

AI model insights. · Write clean, well-documented, and secure code using Python, C C#, or R. · Leverage libraries such as TensorFlow, PyTorch, and Scikit-learn to prototype and optimize AI models. · Communicate complex technical concepts clearly to both technical and non-technical stakeholders. · Stay up-to-date with More ❯

Strong programming skills in python and knowledge of software engineering best practices Strong knowledge of basic data science libraries in Python (NumPy, pandas, scikit-learn, pyspark) Strong knowledge of the main deep-learning frameworks such as PyTorch, TensorFlow, Keras Experience with Linux and shell scripting and experience with More ❯

Active EDV/UK*C security clearance. Proficient in Python and/or R, with experience using data science libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Strong statistical, mathematical, and data modelling skills. Experience with data visualisation tools (e.g., Power BI, Tableau, matplotlib, Plotly). Familiarity More ❯

solution scoping Strong grasp of mathematical, statistical concepts, and machine learning algorithms Proficiency in Python and data science libraries for example NumPy, Pandas, Scikit-learn, Keras SQL proficiency Experience with cloud environments for example Google Cloud Platform Version control management Ability to work efficiently without compromising quality Effective More ❯

and Python. An ability to analyse complex datasets and extract actionable insights. Experience with machine learning and deep learning frameworks (e.g. TensorFlow, PyTorch, Scikit-learn). Skilled in building credible statistical models. Knowledge of various learning algorithms (supervised, unsupervised, reinforcement). Experience with MLOps practices. Demonstrable experience building More ❯

in NLP or classification problems. Hands on experience with ML tools like TensorFlow, PyTorch etc. Experience with data science libraries such as NLTK, Scikit-learn, SciPy, (Sci)SpaCy etc. Excellent problem-solving and programming skills in Python Excellent communication skills Preferred Qualifications & Skills: If you have the following More ❯

Expertise Strong experience in machine learning, deep learning, and statistical analysis. Expertise in Python, with proficiency in ML and NLP libraries such as Scikit-learn, TensorFlow, Faiss, LangChain, Transformers and PyTorch. Experience with big data tools such as Hadoop, Spark, and Hive. Familiarity with CI/CD and More ❯

knowledge of standard machine learning algorithms and statistical methods Proficient in python and its standard data science and ML libraries (e.g., numpy, pandas, scikit-learn, boosting and data visualization libraries) Practical experience in data processing and feature engineering for machine learning applications Ability to write robust production-ready More ❯

or causal inference Proficiency in Python for data analysis and statistical modeling (pandas, numpy, scipy, statsmodels) Familiarity with machine learning libraries such as scikit-learn Experience with SQL for data extraction and manipulation Demonstrated ability to translate analytical findings into business recommendations Track record of successful project delivery More ❯

and SQL, and data analysis libraries (e.g., Pandas, NumPy, SciPy, Tidyverse). Strong knowledge of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, NLTK). Experience with NLP techniques, such as named entity recognition (NER), topic modeling, semantic similarity, and knowledge graph construction. Demonstrated ability to More ❯

and SQL, and data analysis libraries (e.g., Pandas, NumPy, SciPy, Tidyverse). Strong knowledge of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, NLTK). Experience with NLP techniques, such as named entity recognition (NER), topic modeling, semantic similarity, and knowledge graph construction. Demonstrated ability to More ❯

production ready code, architect packages, and make sound architectural and procedural choices for effective shared codebases Python and scientific computing packages (Pytorch, Numpy, Scikit-learn, TensorFlow) Database technologies such as ElasticSearch, Neo4j, and SQL Excellent interpersonal, verbal, and written communication skills A flexible attitude with respect to work More ❯

life science organization is considered an asset. Other skills we are searching for are: Programming Skills: Proficiency in Python, data analytics, deep learning (Scikit-learn, Pandas, PyTorch, Jupyter, pipelines), and practical knowledge of data tools like Databricks, Ray, Vector Databases, Kubernetes, and workflow scheduling tools such as Apache More ❯

management skills. Core technical skills: Strong knowledge of data science fundamentals (Machine Learning methods, Statistics). Fluent in common analytics tools (Python, Pandas, Numpy, ScikitLearn, SQL, etc.) Comfortable to use data visualization libraries (e.g. Seaborn, Matplotlib) Demonstrated initiative, judgment and discretion while handling sensitive information Preferred Qualifications: If you have More ❯

Strong grasp of ML/AI algorithms, including LLMs and automated AI systems - Proficient in Python or R and key frameworks (TensorFlow, PyTorch, scikit-learn) - Skilled in handling large datasets, data wrangling, and statistical modelling - Comfortable working independently on end-to-end ML pipelines - Experienced in visualisation tools More ❯

Strong grasp of ML/AI algorithms, including LLMs and automated AI systems - Proficient in Python or R and key frameworks (TensorFlow, PyTorch, scikit-learn) - Skilled in handling large datasets, data wrangling, and statistical modelling - Comfortable working independently on end-to-end ML pipelines - Experienced in visualisation tools More ❯

in Computer Science, Mathematics, Statistics, or a related field. Solid understanding of probability, statistics, and linear algebra. Proficiency in Python, including libraries like scikit-learn, pandas, seaborn, and matplotlib. Experience writing and optimising SQL queries for data retrieval and manipulation. Ability to communicate complex insights effectively. Detail-oriented 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 ❯