1 to 25 of 98 Remote scikit-learn Jobs in England

in Python (preferred) or R, with experience in SQL for data manipulation and analysis. Strong understanding of machine learning algorithms and frameworks like scikit-learn, TensorFlow, or PyTorch. Experience with cloud platforms (AWS, GCP, or Azure) for model deployment and data processing. Proficiency in data visualisation tools such More ❯

Skills Programming Languages: Strong proficiency in Python, R, and SQL. Familiarity with Spark. Data Manipulation & Analysis: Experience with libraries like Pandas, NumPy, and Scikit-learn for data cleaning, manipulation, and model building. Machine Learning & Statistical Modeling: Solid understanding of supervised and unsupervised learning, feature engineering, model selection, and More ❯

degree in a STEM (Science, Technology, Engineering, or Mathematics) discipline. Strong programming skills in Python, including experience with libraries such as Pandas, NumPy, Scikit-learn, and TensorFlow/PyTorch. Experience with data processing, analysis, and visualization. Knowledge of machine learning techniques and statistical analysis. Familiarity with cloud computing More ❯

degree in a STEM (Science, Technology, Engineering, or Mathematics) discipline. Strong programming skills in Python, including experience with libraries such as Pandas, NumPy, Scikit-learn, and TensorFlow/PyTorch. Experience with data processing, analysis, and visualization. Knowledge of machine learning techniques and statistical analysis. Familiarity with cloud computing More ❯

to aviation industry problems Strong programming skills in Python, R, or similar languages 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 ❯

Hadoop, Kafka, or similar. Timeseries Database: InfluxDB or TimescaleDB, or similar. Cloud Platforms: AWS Redshift, Azure Synapse, or similar. ML/AI Tools: scikit-learn, TensorFlow, PyTorch. Data Visualization: Power BI, Tableau, or similar. Version Control: Git. Preferred Qualifications: Experience with energy management systems or SCADA. Knowledge 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 ❯

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 ❯

that demonstrates some of the qualities we’re looking for. Technical Skills: Strong proficiency in Python and relevant frameworks/libraries (NumPy, Pandas, Scikit-Learn, TensorFlow/PyTorch, LangChain, LangGraph, Hugging Face, etc.). Experience working with LLMs and AI models in production environments. Experience building RAG-based 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 ❯

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 ❯

Python and SQL, with the ability to query databases and manipulate large datasets. Proficiency in key Python libraries for data science, including Pandas, Scikit-learn, Statsmodels, NumPy, SciPy, Matplotlib, TensorFlow, and Keras. Solid understanding of machine learning techniques, such as clustering, tree-based methods, boosting, text mining, and More ❯

experience with evaluation techniques in object detection and classification. Programming Skills: Language: Python Frameworks and libraries: Core python libraries like pandas, numpy, opencv, scikit-learn etc. Pytorch, Keras, Tensorflow, MMdetection (and other common CV libraries). Huggingface. Streamlit (or other alternatives). Cloud Technologies: AWS and knowledge of More ❯

experience with evaluation techniques in object detection and classification Programming Skills Language: Python Frameworks and libraries: Core python libraries like pandas, numpy, opencv, scikit-learn etc Pytorch, Keras, Tensorflow, MMdetection (and other common CV libraries) Huggingface Streamlit (or other alternatives) Cloud Technologies: AWS Knowledge of appropriate services within More ❯

etc.). Proficiency in Python, as well as ML and data analysis libraries: data transformation (pandas, polars, pyspark), gradient boosting & deep learning frameworks, scikit-learn, etc. Knowledge and experience in relational databases, cloud solutions (e.g. Databricks, Azure, GCP, AWS, Snowflake). Experience in writing well-structured code: functions 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 ❯

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 ❯

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 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 ❯

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 ❯

NLP, and LLMs Expert ability with ML/MLOps Experience mentoring/up-skilling more junior team members. Strengths in SQL, Python (Pandas, Scikit-Learn, PyTorch) PhD-level education and experience within Marketing is preferred. Experience in an academic/research background. If you think this opportunity could 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 ❯

work Python: You have built and deployed production-grade Python applications and you are familiar with data science libraries such as pandas and scikit-learn Tooling & Environment: DevOps: You have experience working with DevOps tooling, such as gitops, Kubernetes, CI/CD tools (we use buildkite) and Docker More ❯

work Python: You have built and deployed production-grade Python applications and you are familiar with data science libraries such as pandas and scikit-learn DevOps: You have experience working with DevOps tooling, such as gitops, Kubernetes, CI/CD tools (we use buildkite) and Docker Cloud: You More ❯