1 to 25 of 32 Permanent Matplotlib Jobs

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 ❯

Git, Docker, Kubernetes). Familiarity with AI platforms and frameworks such as LangChain, Llamaindex and, HugginFace. Expertise in data manipulation, data visualisation, and statistical modelling libraries (e.g.: pandas, NumPy, Matplotlib, scikit-learn). Skills in data visualisation tools (e.g.: Tableau, PowerBI). Excellent problem-solving and analytical skills. Skills & attributes Passion for leveraging data to drive social impact and create More ❯

DocumentDB, MongoDB Demonstrated expertise in unit testing and tools - JUnit, Mockito, PyTest, Selenium. Strong working knowledge of the PyData stack - pandas, NumPy for data manipulation; Jupyter Notebooks for experimentation; matplotlib/Seaborn for basic visualisation. Experience with data analysis and troubleshooting data-related issues. Knowledge of design patterns and software architectures Familiarity with CI/CD and automation tools. Experience More ❯

learn) in the following areas: Programming for Data Science (e.g., Python with Pandas, NumPy, R) Statistical Analysis and Hypothesis Testing Data Cleaning, Preprocessing, and Feature Engineering Data Visualization (e.g., Matplotlib, Seaborn, Plotly, Tableau) Machine Learning Fundamentals (e.g., Supervised, Unsupervised Learning) Machine Learning Algorithms (e.g., Regression, Classification, Clustering, Decision Trees, SVMs, Neural Networks) Model Evaluation and Validation Big Data Technologies (e.g. More ❯

learn) in the following areas: Programming for Data Science (e.g., Python with Pandas, NumPy, R) Statistical Analysis and Hypothesis Testing Data Cleaning, Preprocessing, and Feature Engineering Data Visualization (e.g., Matplotlib, Seaborn, Plotly, Tableau) Machine Learning Fundamentals (e.g., Supervised, Unsupervised Learning) Machine Learning Algorithms (e.g., Regression, Classification, Clustering, Decision Trees, SVMs, Neural Networks) Model Evaluation and Validation Big Data Technologies (e.g. More ❯

learn) in the following areas: Programming for Data Science (e.g., Python with Pandas, NumPy, R) Statistical Analysis and Hypothesis Testing Data Cleaning, Preprocessing, and Feature Engineering Data Visualization (e.g., Matplotlib, Seaborn, Plotly, Tableau) Machine Learning Fundamentals (e.g., Supervised, Unsupervised Learning) Machine Learning Algorithms (e.g., Regression, Classification, Clustering, Decision Trees, SVMs, Neural Networks) Model Evaluation and Validation Big Data Technologies (e.g. 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 ❯

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 ❯

Skills & Experience: Bachelor's degree in Computer Science, Mathematics, Statistics, Business Administration or related field Advanced knowledge of SQL 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 ❯

working on or leading customer facing engagements emphasizing quantitative or computational finance. • Experience or familiarity with visualizing multi-dimensional financial data or events, using tools like Tableau, Plotly, ggplot2, matplotlib, seaborn, or D3.js. • Demonstrated ability to manipulate large financial datasets and time series data and perform calculations with at least one modern programming language like Python (utilizing packages like scikit More ❯

related field). 3+ years of experience writing production-grade Python code. 3+ years of hands-on experience with core Python data libraries (e.g., pandas, numpy, sklearn, tensorflow, pytorch, matplotlib). At least 1 year of experience deploying machine learning models in production environments. 1-2 years of experience working with SQL/NoSQL databases (e.g., Elasticsearch, graph databases). More ❯

better business outcomes. Proficiency in mathematical optimization, discrete-event simulation, rules programming, and predictive analytics is essential. Key technologies include Python, PyCharm, VS Code, Jupyter Notebooks, Pandas, NumPy, Dask, Matplotlib, Seaborn, Plotly, shell scripting, and database management with SQL, MongoDB, Cassandra, PostgreSQL, and MySQL. Familiarity with version control systems like Git, GitHub, GitLab, and CI/CD tools such as More ❯

Engineering & Modelling: Understanding of ORM/entity relationships, NoSQL, JSON, XML, SQL and exposure to data visualisation tools (ETL/ELT). Data Science Tools: Proficiency in Numpy, Pandas, Matplotlib, Seaborn and Scikit-learn. MLOps: Experience building pipelines (CI/CD) using Bicep or similar technologies. Expertise in deploying, monitoring and managing machine learning models in production environments. API Development More ❯

with an eagerness to learn 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 Python. Exposure to Azure ecosystem More ❯

understanding of statistical modelling, machine learning, and data mining techniques. Experience with SQL and working with large-scale databases. Familiarity with data visualisation tools (e.g., Power BI, Tableau, or Matplotlib). Exposure to natural language processing (NLP) or geospatial analysis is advantageous. SC clearance or the ability to obtain it (UK residency for at least 5 years is required). More ❯

delivering cross-functional projects. Experience of embedding operation excellence culture within their teams. Knowledge of database modelling, database concepts and SQL Experience with data visualization frameworks like D3.js, Plotly, Matplotlib, or similar Hybrid working applies to this role, with the expectation of 2-3 days per week onsite. We create a place where people can grow, be their best, be More ❯

technical capabilities in a collaborative environment, this is an excellent opportunity to take the next step in your career. Essential Solid programming knowledge with Python Experience using Pandas, NumPy, Matplotlib, and PyTorch Strong understanding of SQL for querying and data manipulation Familiarity with CI/CD workflows and Git version control Detail-oriented and proactive problem solver Enthusiastic about using More ❯

skills regarding data analysis, statistics, and programming. Strong working knowledge of, Python, Hadoop, SQL, and/or R. Working knowledge of Python data tools (e.g. Jupyter, Pandas, Scikit-Learn, Matplotlib). Ability to talk the language of statistics, finance, and economics a plus. Profound knowledge of the English language. In a changing world, diversity and inclusion are core values for More ❯

year. They code in Python, and React on the Frontend. Tech & Data Science stack: Kubernetes & Docker on Google Cloud Python 3: Pandas, RabbitMQ, Celery, Flask, SciPy, NumPy, Dash, Plotly, Matplotlib Javascript, React, Redux PostgreSQL, Redis Prometheus, Alert Manager, DataDog If you joined the company in a Data Science role you would be working on sophisticated pricing algorithms which would enable More ❯

experience in software developement ( Python and C++ )- Academic degree in computer science, mechatronics, electronic engineering, telecommunication engineering or similar qualification, PhD welcome- Experience with Python (numpy/scipy/matplotlib)- Hands-on experience in AWS- Software debugging skills, understanding of performance optimization- Very good understanding of the software development process, preferably in the automotive area- You are hardworking and have More ❯

great relationships with Data Science, Technology, Finance, Collections, Ops and other stakeholders What you'll need Excellent SQL skills Python data science stack (pandas, NumPy, Jupyter notebooks, Plotly/matplotlib, etc) A drive to solve problems using data Experience in a management role What would be a bonus: Familiarity with Git Data visualization tool (Tableau, Looker, PowerBI or equivalent) DBT More ❯

cloud platforms (preferably Azure) and services such as Data Lake, Synapse, Event Hubs, and Functions. Authoring reports and dashboards with either open source or commercial products (e.g. PowerBI, Plot.ly, matplotlib) Programming OOP DevOps Web technologies HTTP/S REST APIs Experience with time-series databases (e.g., InfluxDB, kdb+, TimescaleDB) and real-time data processing. Familiarity with distributed computing and data More ❯

cloud platforms (preferably Azure) and services such as Data Lake, Synapse, Event Hubs, and Functions. Authoring reports and dashboards with either open source or commercial products (e.g. PowerBI , Plot.ly, matplotlib) Programming OOP DevOps Application development lifecycle Web technologies HTTP/S HTML/Javascript REST APIs Authentication protocols Data formats (CSV, JSON, XML, Parquet) Experience with time-series databases (e.g. More ❯

BI dashboards and reports to support business decision-making. Collaborate with stakeholders to gather requirements and translate them into technical solutions. Perform basic data analysis using Python (e.g., pandas, matplotlib) when needed. Ensure data quality, governance, and documentation across all solutions. Provide training and support to end users on BI tools and data literacy. REQUIREMENTS Previous experience as a BI More ❯