26 to 50 of 140 Permanent Matplotlib Jobs

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 ❯

Data Science, Statistics, Mathematics, Computer Science, or a related discipline. Proficiency in Excel for data manipulation, analysis, and reporting. Experience with Python (Pandas, NumPy, Matplotlib, Seaborn) and SQL for data processing and analysis. Familiarity with Power BI and/or Tableau for creating interactive dashboards and reports. An understanding of 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 ❯

with Python libraries like Flask, FastAPI, Pandas, PySpark, PyTorch, to name a few. Proficiency in statistics and/or machine learning libraries like NumPy, matplotlib, seaborn, scikit-learn, etc. Experience in building ETL/ELT processes and data pipelines with platforms like Airflow, Dagster, or Luigi. What's important for 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 ❯

connecting and integrating data sets for accurate and comprehensive analysis Proficiency in using common data science Python packages (e.g. Pandas, NumPy, Scikit-learn and Matplotlib) for data manipulation, analysis, and visualisation Familiarity with advanced data science techniques, including machine learning (e.g., K-means), natural language processing (e.g., NLTK or spaCy 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 ❯

NumPy), Exploratory Data Analysis. Je hebt een affiniteit voor verschillende machine learning-algoritmen, zoals regressie, classificatie, clustering en deep learning. Een eerste ervaring met Matplotlib, Seaborn, of Tableau en met big data technologieën (Hadoop, Spark of NoSQL databases) is een plus. Je bent vertrouwd met databases en query-talen zoals More ❯

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 More ❯

as PyCharm, VS Code, and Jupyter Notebooks. It includes expertise in data manipulation using tools like Pandas, NumPy, and Dask, and data visualization with Matplotlib, Seaborn, and Plotly. Scripting abilities in shell scripting, along with experience in managing databases like SQL, MongoDB, Cassandra, PostgreSQL, and MySQL, are also included. Additionally More ❯

complex problems. Data Science Experience: - Extensive knowledge of data preprocessing, feature engineering, and model evaluation techniques. - Experience with data visualization tools and libraries (e.g., Matplotlib, Seaborn, Plotly). - Familiarity with statistical analysis and machine learning algorithms. Distributed Computing: - Experience in deploying and managing distributed machine learning workloads. - Knowledge of distributed More ❯

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 More ❯

similar. Knowledge of data science concepts: data preparation, exploration, modeling, applicable to structured or unstructured data. Experience with data science tools like Jupyter, pandas, matplotlib, seaborn, numpy. Experience with API testing and security tools such as Postman, Burp Suite, OWASP ZAP. Knowledge of database management systems like 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 ❯

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 ❯

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 More ❯

the ability to apply this process when handling structured or unstructured data Confident with using common data science tooling such as Jupyter notebooks, pandas, matplotlib, seaborn, numpy API testing and security tools: Postman, Burp Suite, OWASP ZAP, etc. Strong knowledge of database management systems (DBMS) such as MySQL Hands-on More ❯

the ability to apply this process when handling structured or unstructured data Confident with using common data science tooling such as Jupyter notebooks, pandas, matplotlib, seaborn, numpy API testing and security tools: Postman, Burp Suite, OWASP ZAP, etc. Strong knowledge of database management systems (DBMS) such as MySQL Hands-on More ❯