1 to 25 of 56 Matplotlib Jobs

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 ❯

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 ❯

of mathematics and statistics. Experience with machine learning frameworks like TensorFlow, Keras, or PyTorch. Knowledge of data analysis and visualization tools (e.g., Pandas, NumPy, Matplotlib). Familiarity with big data technologies (e.g., Hadoop, Spark). Excellent problem-solving skills and attention to detail. Ability to work independently and as part More ❯

modeling and simulation Experience building or refining machine learning models Demonstrated experience with the following python packages: Pandas, Numpy, Pytorch or Tensorflow, Sklearn, Pyodbc, Matplotlib, and Seaborn. Experience with a large variety of programing languages: Matlab, SQL, C#, Javascript, VBA Experience deploying data pipelines Ability to develop experimental and analytical 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 ❯

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 ❯

data analysis. Experience with libraries like Pandas, NumPy, and scikit-learn for data manipulation and model building. Familiarity with data visualization tools such as Matplotlib or Plotly. Machine Learning & Model Development Experience developing and fine-tuning machine learning models, including supervised and unsupervised learning. Applied knowledge of deep learning frameworks More ❯

learn, TensorFlow, PyTorch). • Proficiency in data manipulation and analysis (e.g., Pandas, NumPy, Spark). • Knowledge of data visualization tools (e.g., Power BI, Tableau, Matplotlib). • Understanding of statistical modelling, hypothesis testing, and A/B testing. • Experience with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies. • Ability More ❯

proficiency in data manipulation libraries (e.g., Pandas, NumPy). Experience with machine learning frameworks (e.g., Scikit-Learn, TensorFlow) and data visualization tools (e.g., Tableau, Matplotlib). Solid understanding of statistics, probability, and data-driven decision-making. Experience working with databases (SQL) and data warehousing solutions. Strong problem-solving skills and More ❯

techniques. Familiarity with actuarial methods and tools (e.g., pricing, reserving, financial forecasting). Knowledge of data visualization techniques and tools (e.g., Tableau, Power BI, matplotlib). Experience with cloud-based platforms (AWS, Azure) and big data tools (Hadoop, Spark) is a plus. Educational Background : A degree in Actuarial Science, Mathematics More ❯

the ability to clean and transform data in preparation for analysis or modelling. Data visualisation - using tools like Power BI, Tableau, or libraries like Matplotlib or Seaborn to tell stories. Statistical analysis - understanding of key statistics and distributions, hypothesis testing, and the ability to derive insights. Working with both structured 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 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 ❯

Amazon AWS or Microsoft Azure. Familiarity with containerization technologies like Docker and Kubernetes. Working experience in Data Visualization tools such as Tableau, Power BI, matplotlib, seaborn, and Plotly. Experience developing CI/CD components for production-ready data pipelines. Experience working with big data and/or MPP (massively parallel 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 ❯

algorithms for power grid problems on top of standard optimization libraries. Familiarity with data science libraries such as NumPy, Pandas, and visualization tools (e.g., Matplotlib, Seaborn). Experience with cloud computing platforms (e.g., Google Cloud Platform, AWS, Azure) and containerization technologies (e.g., Docker, Kubernetes). Experience contributing to open-source More ❯

a notebook-based data science environment (JupyterHub). Experience in advanced Python data science packages (Pandas, NetworkX, Scikit-Learn, PyTorch or TensorFlow/Keras, Matplotlib or Plotly, etc.) _ Compensation ranges encompass a total compensation package and are a general guideline only and not intended as a guaranteed and/or More ❯

Machine Learning and Data Science such as TensorFlow, PyTorch, and scikit-learn. Computer vision. Data Science and Visualisation libraries including Pandas, NumPy, scikit-learn, matplotlib, Seaborn. Cloud services used in machine learning and data science, such as Azure, OpenAI, Hugging Face, AWS ML/AI. Machine Learning Applications development life 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 ❯

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 ❯

models, clustering algorithms, classification models and time series techniques in a production environment. Proficiency with Python and all related Data Science libraries (numpy, pandas, matplotlib, etc.), and SQL with excellent analytical and algorithmic skills. A proven record for successful implementation of translating business requirements into a technical solution. Multi-tasking More ❯

Experience with various machine learning libraries (i.e. Apache Spark, Scikit-learn, XGBoost, etc.) Experience with various data manipulation and pipeline libraries (i.e. Pandas, Polars, matplotlib, Plotly, numpy, scipy, etc.)Experience with data science environments (e.g. Jupyter Notebook, Data Bricks, or Amazon Sage Maker) Experience with Python, R, and/or More ❯

large-scale data warehouses (Snowflake, Redshift, Presto). Proficiency in data visualization tools (Databricks, PowerBI) and the Python data science ecosystem (Jupyter, Pandas, Numpy, Matplotlib). Plusses: Financial services background Degree in cybersecurity Any advanced Data bricks qualifications Have lead teams of more than 10 people Recent involvement in a More ❯

large-scale data warehouses (Snowflake, Redshift, Presto). Proficiency in data visualization tools (Databricks, PowerBI) and the Python data science ecosystem (Jupyter, Pandas, Numpy, Matplotlib). Plusses: Financial services background Degree in cybersecurity Any advanced Data bricks qualifications Have lead teams of more than 10 people Recent involvement in a More ❯

large-scale data warehouses (Snowflake, Redshift, Presto). Proficiency in data visualization tools (Databricks, PowerBI) and the Python data science ecosystem (Jupyter, Pandas, Numpy, Matplotlib). Plusses: Financial services background Degree in cybersecurity Any advanced Data bricks qualifications Have lead teams of more than 10 people Recent involvement in a More ❯