1 to 25 of 274 scikit-learn Jobs in England

understanding of statistical analysis and modeling techniques, including linear regression, time series, decision trees, and clustering algorithms. Proficient in machine learning libraries (e.g., Scikit-learn, TensorFlow, PyTorch, Keras) for building and deploying predictive models. Proficient in Python, R, or similar programming languages for data analysis and machine learning. More ❯

techniques to aviation industry problems Strong programming skills in Python, R, or similar for data analysis Experience with machine learning libraries and frameworks (scikit-learn, TensorFlow, PyTorch) Proficiency in SQL and experience working with large, complex datasets Knowledge of statistical analysis, experiment design, and modeling techniques Understanding of 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 ❯

with data engineering concepts and tools (ETL pipelines, data warehousing - they are using SnowFlake). Knowledge of machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow). Bachelor's degree in Computer Science, Statistics, Mathematics, or related field. Technical Skills: Data manipulation: Pandas, NumPy. Data engineering: Snowflake, Apache 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 ❯

SQL. Experience with machine learning techniques, including supervised and unsupervised learning, and deep learning. Proficiency in data analysis libraries such as pandas, numpy, scikit-learn, or TensorFlow. Familiarity with data visualisation tools (e.g., Tableau, Power BI, Matplotlib). Experience working with cloud platforms (AWS, Azure, GCP) and big 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

in data science, machine learning, or a related role Proficiency in programming languages such as Python or R, and libraries like TensorFlow, PyTorch, Scikit-learn, or Pandas Strong understanding of statistical modeling, probability, and optimization techniques Ability to work with messy, real-world datasets and perform feature engineering More ❯

in data science, machine learning, or a related role Proficiency in programming languages such as Python or R, and libraries like TensorFlow, PyTorch, Scikit-learn, or Pandas Strong understanding of statistical modeling, probability, and optimization techniques Ability to work with messy, real-world datasets and perform feature engineering 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 ❯

programming skills as evidenced by earlier work in data science or software engineering, including experience with standard libraries for data science (NumPy, Pandas, Scikit-Learn etc). Generalist expertise across the entire data lifecycle including data strategy, data governance, risk and ethics, architecture, modelling. Technology implementation including data 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 ❯

and interpretation. Proficiency in Object-Oriented programming in Python with expertise in key data science and machine learning libraries (e.g. TensorFlow, PyTorch and Scikit-Learn). Expertise in cloud technologies (emphasis on Azure and/or AWS) and deployment practices, ensuring seamless and scalable delivery. Proven track record More ❯

and help build the data science community. What we're looking for: A strong data science background including solid coding skills with Python Scikit learn, Pandas, Matplotlib, Numpy, Tensorflow, Keras Statistics (including statistical tests) Good knowledge of traditional Machine Learning techniques (Deep Learning and Reinforcement Learning a definite 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 ❯