1 to 25 of 450 scikit-learn Jobs in the UK

Advanced Python programming skills, with a strong emphasis on writing efficient, scalable, and maintainable code. Proven experience with TensorFlow/PyTorch/Jax, Scikit-learn, and MLOps workflows for training, deployment, and monitoring of ML models. Experience working with Polars and/or Pandas for high-performance data More ❯

Advanced Python programming skills, with a strong emphasis on writing efficient, scalable, and maintainable code. Proven experience with TensorFlow/PyTorch/Jax, Scikit-learn, and MLOps workflows for training, deployment, and monitoring of ML models. Experience working with Polars and/or Pandas for high-performance data More ❯

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 ❯

software engineering skills, including version control (Git), code reviews, and unit testing. Familiarity with common data science libraries and tools (e.g., NumPy, Pandas, Scikit-learn, Jupyter). Experience in setting up and managing continuous integration and continuous deployment pipelines. Proficiency with containerization technologies (e.g., Docker, Kubernetes). Experience More ❯

software engineering skills, including version control (Git), code reviews, and unit testing. Familiarity with common data science libraries and tools (e.g., NumPy, Pandas, Scikit-learn, Jupyter). Experience in setting up and managing continuous integration and continuous deployment pipelines. Proficiency with containerization technologies (e.g., Docker, Kubernetes). Experience 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 ❯

technical and non-technical stakeholders through effective data visualisation and building of reporting frameworks Comfortable with Python data science libraries such as pandas, scikit-learn, numpy, statsmodels Strong SQL experience including analytic functions, performance tuning, data wrangling Ability to work collaboratively and proactively in a fast-paced environment More ❯

to fine-tune those models e.g. XGBoost, Deep Neural Networks, Transformers, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, Pytorch, scikit-learn, etc. Must demonstrate the capacity of reading, understanding and implementing new techniques in the field of machine learning as they emerge. Experience of More ❯

general programming languages: Python, C++, Java, etc. Experience with deep learning, machine learning and NLP frameworks such as PyTorch (or TensorFlow), HuggingFace Transformer, Scikit-learn Experience with working in Linux A strong intuition for what makes products a joy to use Empathy for how different users will need 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 ❯

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 ❯

Maths, Stats, Computer Science, Engineering, etc.) from a top university. Strong foundation in statistics, probability, and applied mathematics. Proficiency in Python (Pandas, NumPy, Scikit-learn). Experience with cloud platforms (AWS, Azure, or GCP) for data processing or model deployment. Familiarity with SQL and relational databases. Exposure to More ❯

and deploying AI solutions in a business environment. Proficiency in Python and familiarity with AI frameworks and libraries such as Pandas, NumPy, PyTorch, Scikit-Learn, Streamlit, and SciPy. Strong understanding of software development principles, AI engineering, and MLOps. Experience working with cloud-based AI solutions on platforms like More ❯

and deploying AI solutions in a business environment. Proficiency in Python and familiarity with AI frameworks and libraries such as Pandas, NumPy, PyTorch, Scikit-Learn, Streamlit, and SciPy. Strong understanding of software development principles, AI engineering, and MLOps. Experience working with cloud-based AI solutions on platforms like 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 ❯

domains (e.g. Natural Language Processing, Computer Vision) and expert knowledge in statistics. You are proficient in the Python Machine Learning stack (NumPy, pandas, scikit-learn, TensorFlow/PyTorch), have extensive experience in software development and are skilled with various database systems (relational/NoSQL). You are experienced More ❯

experience of large-scale data analysis and hypothesis testing. Strong proficiency in statistical analysis and predictive modeling. Proficient in Python (pandas, scipy, numpy, scikit-learn) or R (tidyverse/data.table), along with SQL. Excellent problem-solving skills and attention to detail. Strong communication skills with the ability to More ❯

MATLAB/Simulink, Modelica, Ansys, or equivalent platforms) for modeling BESS components. Strong understanding of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Experience with Linux command-line. Cloud Platforms: Hands-on experience with cloud-based environments such as AWS, Azure, or GCP. Knowledge of 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 ❯

Proficiency in Python programming language Expertise in a programming language (Python preferred) Familiar with data processing and analysis tools such as Pandas, NumPy, Scikit-learn, etc. Knowledge of machine learning concepts such as supervised and unsupervised learning, classification, regression, clustering, dimensionality reduction, etc. Experience with applying machine learning More ❯

to internal initiatives such as blogs, thought leadership, and leading technical forums. Requirements Substantial experience with Python and relevant libraries (e.g. Pandas, Numpy, Scikit Learn, PyTorch, Tensorflow). Experience driving ML & data science solutions into production. You can put the numbers into a business perspective - you're a More ❯

advisory, design & implementation. Contribute to internal initiatives such as blogs & technical forums. Requirements Substantial experience with Python and relevant libraries (e.g. Pandas, Numpy, Scikit Learn, PyTorch, Tensorflow). Experience driving ML & data science solutions into production. You can put the numbers into a business perspective - you're a More ❯

s degree in Data Science, Statistics, Computer Science, Mathematics, or Engineering - or equivalent. Proficiency in Python and relevant data science libraries (NumPy, pandas, scikit-learn, etc.). Experience with SQL, Power BI, Git & GitHub. Strong knowledge of Machine Learning Algorithms and respective theory. Ability to work within a More ❯

s degree in Data Science, Statistics, Computer Science, Mathematics, or Engineering – or equivalent. Proficiency in Python and relevant data science libraries (NumPy, pandas, scikit-learn, etc.). Experience with SQL, Power BI, Git & GitHub. Strong knowledge of Machine Learning Algorithms and respective theory. Ability to work within a 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 ❯