1 to 25 of 120 scikit-learn Jobs in London

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

to become a fluent Python programmer in a short timeframe An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid More ❯

development. Machine Learning (ML): Deep understanding of machine learning principles, algorithms, and techniques. Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. Proficiency in data preprocessing, feature engineering, and model evaluation. Knowledge of ML model deployment and serving strategies, including containerization and More ❯

oriented programming concepts. Experience in designing and implementing ETL pipelines, data warehousing, and data modeling. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Expertise in statistical modeling, machine learning algorithms, and data mining techniques. Familiarity with data visualization and reporting tools, such as Tableau, Power More ❯

development. Machine Learning (ML): • Deep understanding of machine learning principles, algorithms, and techniques. • Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. • Proficiency in data preprocessing, feature engineering, and model evaluation. • Knowledge of ML model deployment and serving strategies, including containerization and More ❯

strong programming skills in languages like Python, R, or other statistical programming tools. Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn is essential to successfully build and deploy models. Additionally, you should have a solid understanding of statistical analysis techniques, including hypothesis testing, regression More ❯

and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms - demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure, Google Cloud) including Cloud provisioning tools (e.g. Terraform). 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 ❯

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 ❯

MS 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 More ❯

We prioritise clean, well-tested code with a culture of documentation and knowledge sharing. Our tech stack includes GCP, Python, GitHub, PyTorch, TensorFlow, Scikit-learn, and XGBoost. With mature infrastructure and dedicated teams for Data Engineering, Analytics, and Platform Engineering, our Data Scientists enjoy high autonomy. We tackle More ❯

years experience in Data Science(perfect for second-jobbers) First-class STEM degree from a prestigious university Strong Python skills (Pandas, NumPy, Scikit-Learn) Cloud computing experience (primarily Azure but they work with all major cloud providers depending on their clients needs). SQL knowledge and database experience More ❯

years experience in Data Science(perfect for second-jobbers) First-class STEM degree from a prestigious university Strong Python skills (Pandas, NumPy, Scikit-Learn) Cloud computing experience (primarily Azure but they work with all major cloud providers depending on their clients needs). SQL knowledge and database experience More ❯

general SQL knowledge is more important). Familiarity with latest Data Science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and frameworks (e.g. Tensorflow, MXNet, scikit-learn). Knowledge of software engineering practices (coding practices to DS, unit testing, version control, code review). Experience with Hadoop (especially the Cloudera More ❯

such as STEM subject or Economics). Proficiency in Python, with a solid understanding of Python libraries (such as NumPy, pandas, Polars, and scikit-learn) for data manipulation and statistical modeling. A minimum of 5 years experience working with Futures order book market data, with strong familiarity in More ❯

databases, software engineering, cloud computing especially AWS) and data science (machine learning processes). Proficiency in Python and frameworks such as PyTorch, TensorFlow, scikit-learn, with some knowledge of LangChain, RAGAS, and CI/CD. Growth mindset and eagerness to learn new challenges. Willingness to travel and 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 ❯