1 to 25 of 80 Matplotlib Jobs in London

natural language processing (NLP) techniques. Data Visualisation and Communication: Advanced skills in data visualisation using tools such as Tableau, Power BI, or libraries like Matplotlib and Seaborn to effectively communicate insights to stakeholders. Ability to present complex technical concepts to non-technical audiences clearly and effectively. Big Data Technologies : Familiarity More ❯

Skilled in handling large datasets, data wrangling, and statistical modelling - Comfortable working independently on end-to-end ML pipelines - Experienced in visualisation tools (e.g. Matplotlib, Seaborn, Tableau) Desirable: - Exposure to cloud platforms (AWS, GCP, Azure) and big data tools (Hadoop, Spark) - MSc/PhD in Computer Science, AI, Data Science More ❯

datasets, data wrangling, and data preprocessing. Experience in data science, statistical modelling, and data analytics techniques. Experience with data analysis and visualization tools (e.g., Matplotlib, Seaborn, Tableau). Ability to work independently and lead projects from inception to deployment. Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms More ❯

tools such as Airflow or Luigi. Experience with message brokers (e.g., RabbitMQ, Kafka) for real-time data processing. Experience with data visualisation libraries (e.g., Matplotlib, Seaborn, Plotly) is a plus. Knowledge of ORM libraries like SQLAlchemy or Django ORM. Familiarity with containerization tools like Docker. Experience with testing frameworks like More ❯

and industry trends. Preferred Qualifications: Experience with API integrations and working with RESTful APIs. Knowledge of data visualization tools (e.g., Tableau, Power BI, or Matplotlib/Seaborn). Familiarity with version control systems (e.g., Git). Experience with containerization tools (e.g., Docker, Kubernetes). Past experiences working in Fintech, Financial More ❯

NLP techniques for text analysis, classification, and information extraction. Knowledge of deep learning frameworks such as PyTorch or TensorFlow. Experience with data visualization tools (Matplotlib, Seaborn, Plotly, or similar). Strong analytical mindset with a focus on solving real-world problems. Excellent communication skills to present findings to technical and More ❯

tools such as Airflow or Luigi. Experience with message brokers (e.g., RabbitMQ, Kafka) for real-time data processing. Experience with data visualisation libraries (e.g., Matplotlib, Seaborn, Plotly) is a plus. Knowledge of ORM libraries like SQLAlchemy or Django ORM. Familiarity with containerization tools like Docker. Basic understanding of front-end More ❯

Data Manipulation & Analysis: Proficient in data manipulation and analysis using tools like Pandas, NumPy, and Jupyter Notebooks. Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau to communicate insights effectively. Our offer: Cash: Depends on experience Equity : Generous equity package, on a standard vesting schedule Impact & Exposure : Work More ❯

Solid understanding and proficiency in working with Pandas, NumPy, Scikit-Learn, TensorFlow, and PyTorch, SQL. Proficiency in advanced data visualization tools and libraries (e.g., Matplotlib, Seaborn, Plotly, Tableau) for creating insightful and interactive visualizations. Solid understanding of data structures, data modelling, and software architecture. Experience with cloud services (such as More ❯

Solid understanding and proficiency in working with Pandas, NumPy, Scikit-Learn, TensorFlow, and PyTorch, SQL. Proficiency in advanced data visualization tools and libraries (e.g., Matplotlib, Seaborn, Plotly, Tableau) for creating insightful and interactive visualizations. Solid understanding of data structures, data modelling, and software architecture. Experience with cloud services (such as More ❯

in Python for developing machine learning models and conducting statistical analyses Strong understanding of data visualization tools and techniques (e.g., Python libraries such as Matplotlib, Seaborn, Plotly, etc.) and the ability to present data effectively Specific technical requirements: Data Science or AI/ML strategy Data Science or AI/ More ❯

machine learning frameworks (e.g., TensorFlow, PyTorch). • Proficiency in Python, R, or other relevant programming languages. • Experience with data analysis and visualization tools (e.g., Matplotlib, Seaborn, Tableau). • Ability to work independently and lead projects from inception to deployment. • MSc or PhD in Computer Science, Artificial Intelligence, or related field More ❯

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 document processing Generative More ❯

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 the following characteristics, it would be a plus: PhD - in a More ❯

Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets More ❯

with cloud platforms such as AWS, Azure, or Google Cloud for AI model deployment. Data Visualisation: Ability to present insights effectively using tools like Matplotlib, Seaborn, Tableau, or Power BI. Model Deployment: Understanding of MLOps principles, APIs, and containerization (Docker, Kubernetes) for productionizing AI models. Business-Focused AI Application: Ability More ❯

with relevant analytical and machine learning libraries (e.g., pandas, polars, numpy, sklearn, TensorFlow/Keras, PyTorch, etc.), in addition to visualization and API libraries (matplotlib, plotly, streamlit, Flask, etc). Experience developing and implementing quantitative models from data in a financial context. Proficiency working with version control systems such as More ❯

with cloud platforms such as AWS, Azure, or Google Cloud for AI model deployment. Data Visualisation: Ability to present insights effectively using tools like Matplotlib, Seaborn, Tableau, or Power BI. Model Deployment: Understanding of MLOps principles, APIs, and containerization (Docker, Kubernetes) for productionizing AI models. Business-Focused AI Application: Ability More ❯

Learning & Deep Learning – Algorithms, neural networks, and frameworks like TensorFlow or PyTorch. Data Analysis & Visualization – Ability to work with large datasets using Pandas, NumPy, Matplotlib, or Seaborn. NLP & Computer Vision (Bonus) Software Development – Knowledge of APIs, backend systems, and full-stack development (desirably for AI-powered applications). Cloud & DevOps More ❯

and contribute within a team setting. Technical Experience Proficient in Python for data analysis, including use of key libraries (e.g. Pandas, NumPy, Scikit-learn, Matplotlib). Good working knowledge of SQL for querying and transforming structured data. Basic understanding of common machine learning techniques and ability to implement them in More ❯

and contribute within a team setting. Technical Experience: Proficient in Python for data analysis, including use of key libraries (e.g. Pandas, NumPy, Scikit-learn, Matplotlib). Good working knowledge of SQL for querying and transforming structured data. Basic understanding of common machine learning techniques and ability to implement them in More ❯

clients.+ Strong proficiency in programming languages such as Python, R, and SQL.+ In-depth experience with data manipulation and visualization libraries (e.g., Pandas, NumPy, Matplotlib, etc.).+ Solid understanding of big data technologies (e.g., Hadoop, Spark) and cloud platforms (AWS, Azure, Google Cloud).+ Strong expertise in the full data More ❯

processing techniques, feature engineering, and model evaluation metrics. Proven ability to manipulate, query and visualise data and training/evaluation results (using e.g., Pandas, Matplotlib, Seaborn). Proven understanding of Information Extraction and Retrieval techniques. Proven understanding of NLP and large language models. Proven understanding of database concepts (differences between More ❯

science concepts such as data preparation, exploration, modeling, applicable to structured and unstructured data. Experience with data science tools such as Jupyter notebooks, pandas, matplotlib, seaborn, numpy. Familiarity with API testing and security tools like Postman, Burp Suite, OWASP ZAP. Knowledge of database management systems such as MySQL. Hands-on More ❯

in building and maintaining efficient data pipelines to support data science initiatives. Data Visualization : Expertise in using visualization tools (e.g., Power BI, Tableau, or matplotlib) to present complex data insights. End-to-End Project Delivery : Proven experience taking a data science project from concept to deployment, including model evaluation and More ❯