1 to 25 of 78 Matplotlib Jobs in London

frameworks (TensorFlow, PyTorch, scikit-learn) - 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, or related field More ❯

and predictive modeling. Experience with 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 non-technical stakeholders. Fluent in More ❯

to validate models and algorithms. 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 at the leading edge of More ❯

to validate models and algorithms. 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 at the leading edge of More ❯

scikit-learn. Skilled in data wrangling, preprocessing, and managing large-scale datasets. Solid understanding of statistical modelling, predictive analytics, and time series analysis. Experience with data visualisation tools like Matplotlib, Seaborn, or Tableau. Salary: £525 per day #J-18808-Ljbffr More ❯

Clustering Dimensionality reduction LLM Proficiency 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/ML solution architecture Proficiency in More ❯

Python programming skills, including experience with relevant analytical and machine learning libraries (e.g., pandas, polars, numpy, sklearn, TensorFlow/Keras, PyTorch, etc.), in addition to visualisation and API libraries (matplotlib, plotly, streamlit, Flask, etc). Understanding of Gen AI models, Vector databases, Agents, and follow the market trends. Its desirable to have a hands-on experience on these. Substantial experience More ❯

Python programming skills, including experience with relevant analytical and machine learning libraries (e.g., pandas, polars, numpy, sklearn, TensorFlow/Keras, PyTorch, etc.), in addition to visualisation and API libraries (matplotlib, plotly, streamlit, Flask, etc). Understanding of Gen AI models, Vector databases, Agents, and follow the market trends. Its desirable to have a hands-on experience on these. Substantial experience More ❯

production-grade code in Python. 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 AWS) and tools for machine More ❯

and Scikit-learn. • Experience with machine learning frameworks like TensorFlow or PyTorch. • Strong SQL skills and experience with relational databases. • Proficiency in data visualization tools such as Power BI, Matplotlib, Seaborn, or Plotly. • Experience with cloud platforms, especially AWS (e.g., S3, EC2, SageMaker). • Familiarity with tools like Jupyter, Snowflake, Docker, and Atlassian suite (Bitbucket, JIRA, Confluence). Soft Skills More ❯

computer science , Mathematics, Statistics, Business Administration or related field Advanced knowledge of SQL (joins, aggregations, CTEs and window functions) Good knowledge of Python, including popular Data Science packages (pandas, matplotlib, seaborn, numpy , sklearn ) Familiarity with what is happening under the hood of popular Machine Learning algorithms Strong problem-solving skills and attention to detail Strong communication and collaboration skills Ability More ❯

probability, bayesian stats etc.) Good 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 AI (open and closed source More ❯

s degree from a Russell 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 A passion for solving complex More ❯

s degree from a Russell 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 A passion for solving complex More ❯

knowledge of data science fundamentals (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 STEM subject and experience in More ❯

learn, XGBoost, LightGBM, StatsModels PyCaret, Prophet, or custom implementations for time series A/B testing frameworks (e.g., DoWhy, causalml) Programming & Data Tools : Python: Strong foundation in Pandas, NumPy, matplotlib/seaborn, scikit-learn, TensorFlow, Pytorch etc. SQL: Advanced querying for large-scale datasets. Jupyter, Databricks, or notebooks-based workflows for experimentation. Data Access & Engineering Collaboration : Comfort working with cloud More ❯

and learning more about key areas/topics in AI research. Python for Data Analysis: Proficiency in Python and common data analysis libraries (e.g., Pandas, NumPy, SciPy, Scikit-learn, Matplotlib/Seaborn). Data Visualization/Dashboarding: Experience creating effective dashboards and visualizations using tools like Tableau, Looker, Google Data Studio, or similar. Analytics Engineering: Experience designing and implementing ELT More ❯

and data science solutions for 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 science lifecycle: data collection, preprocessing More ❯

plus). Experience with version control (git) and testing. Strong foundation in statistics and probability. Knowledge of data science algorithms: classification, regression, clustering. Data visualization skills using libraries like matplotlib, seaborn, plotly. Data management skills: pandas, numpy, scipy. Experience with AWS cloud services (SageMaker, S3, EC2, EMR, Glue). Experience with LLM frameworks (LangChain, LangGraph) is a plus. What We More ❯

Requirements You have a strong ability to analyze and interpret large datasets, uncovering meaningful trends and insights. You are proficient in SQL and experienced in using Python (pandas, numpy, matplotlib, seaborn) for exploratory data analysis and data visualization. Big plus is practical familiarity with the big data stack (Spark, Presto/Athena, Hive). You have experience with BI tools More ❯

preferred). Experience in data preprocessing 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 graph/relational/non More ❯

statistics Experienced with containerisation (Docker, Kubernetes) Knowledge of cloud architecture, API design, security, deployment Hands-on with at least one major cloud platform Data visualization skills with Plotly and Matplotlib Creative problem solver with attention to detail Excellent communication skills Comfortable in a dynamic, high-growth environment Preferred Qualifications MS or Ph.D. in relevant fields Understanding of marketing ecosystem and More ❯

with a good understanding of best practices in software engineering and data engineering • Practical object-oriented programming experience in Python with knowledge of relevant packages including Pandas, NumPy, SciPy, Matplotlib, Scikit-learn, Pytorch • In-depth knowledge of statistical and machine learning models as well as experience with end-to-end delivery lifecycles • Experience in writing clean and maintainable code for More ❯

environment Ability to work in a team with fast turnarounds, manage workloads effectively and readily assume additional responsibilities Exposure to data analysis libraries (e.g., pandas, numpy) and visualisation tools (Matplotlib, plotly) Understanding software testing principals and frameworks Preferred skills Knowledge of financial instruments and equity markets Familiarity with cloud services Familiarity with quantitative research methodologies or keen interest in financial More ❯

and model development. Experience in working with large-scale datasets and utilizing big data technologies (e.g., Azure, Databricks, Spark) Familiarity with data visualization tools such as Power BI, or matplotlib Strong knowledge of predictive modeling, machine learning techniques, and statistical analysis. Soft Skills Analytical mindset with a passion for uncovering actionable insights from complex datasets. Excellent communication and presentation skills More ❯