1 to 25 of 29 Permanent Seaborn Jobs in England

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 ❯

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 ❯

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 ❯

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 Services More ❯

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 Services More ❯

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 ❯

concepts and methodologies. Data Manipulation & Analysis: Proficiency with tools like Pandas, NumPy, and Jupyter Notebooks. Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau. More ❯

concepts and methodologies. Data Manipulation & Analysis: Proficiency with tools like Pandas, NumPy, and Jupyter Notebooks. Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau. More ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 and More ❯

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 ❯

Measure Killer) Proficiency in other data visualisation tools beyond Power BI (e.g., Tableau, Looker, ThoughtSpot), as well as data visualisation libraries (e.g., Matplotlib, Seaborn, Plotly, ggplot2, D3.js, Kepler.gl, Apache Superset, Streamlit). Expertise in data storytelling techniques and the ability to translate data into actionable insights through compelling More ❯

statsmodels NLP & ML Frameworks: spaCy, Hugging Face Transformers, TensorFlow or PyTorch (where applicable) Data Engineering & Pipelines: dbt, Airflow, SQL, Spark, Dask Visualisation: Plotly, Seaborn, Matplotlib, Dash, Streamlit Dev & Collaboration Tools: Jupyter, Git, Docker, VS Code, CI/CD tools Ideal but Not Required: Fluency in French or German More ❯

Proficiency in Python, SQL, and NoSQL databases (e.g., PostgreSQL, MongoDB). Experience with data visualisation tools (Tableau, Power BI, or Python libraries like Seaborn). Familiarity with FastAPI for system integration and automation. API Integration Salesforce (or tools like MuleSoft) for CRM data extraction. Email APIs (e.g., Microsoft More ❯

Proficiency in Python, SQL, and NoSQL databases (e.g., PostgreSQL, MongoDB). Experience with data visualisation tools (Tableau, Power BI, or Python libraries like Seaborn). Familiarity with FastAPI for system integration and automation. API Integration Salesforce (or tools like MuleSoft) for CRM data extraction. Email APIs (e.g., Microsoft More ❯

Tech stack: Machine Learning Engineer, Python, TensorFlow, PyTorch, scikit-learn, Keras, Natural Language Processing (NLP), Hugging Face Transformers, Pandas, NumPy, Jupyter Notebooks, Matplotlib, Seaborn, Flask (for building APIs), FastAPI, Docker, MLflow, DVC (Data Version Control), AWS SageMaker, Azure Machine Learning, Google Cloud AI Platform, TensorFlow Serving, ONNX (Open More ❯

Impala or other SQL-on-Hadoop query engines. Understanding of web development concepts (HTML, CSS, JavaScript). Proficiency in data visualization libraries (Plotly, Seaborn). Solid understanding of database design principles and normalization. Experience with ETL tools and processes and Apache Oozie or similar workflow management tools. Understanding More ❯

from heterogeneous multi-dimensional datasets. Ability to apply machine learning techniques (e.g., scikit-learn, PyTorch, TensorFlow) and present complex data visually using Matplotlib, seaborn, or Streamlit. Fluent in Python, with experience working with data processing libraries such as Pandas. Strong SQL skills, a good understanding of Linux, parallel More ❯

Experienced in using Python and SQL to query and analyse large datasets, with expertise in libraries such as Pandas, NumPy, SciPy, Matplotlib, and Seaborn for data manipulation, statistical analysis, and visualisation. Familiarity with Monte Carlo simulations in Python and/or PyMC3 for Bayesian modelling is a plus. More ❯

Experienced in using Python and SQL to query and analyse large datasets, with expertise in libraries such as Pandas, NumPy, SciPy, Matplotlib, and Seaborn for data manipulation, statistical analysis, and visualisation. Familiarity with Monte Carlo simulations in Python and/or PyMC3 for Bayesian modelling is a plus. More ❯

Experienced in using Python and SQL to query and analyse large datasets, with expertise in libraries such as Pandas, NumPy, SciPy, Matplotlib, and Seaborn for data manipulation, statistical analysis, and visualisation. Familiarity with Monte Carlo simulations in Python and/or PyMC3 for Bayesian modelling is a plus. More ❯

Experienced in using Python and SQL to query and analyse large datasets, with expertise in libraries such as Pandas, NumPy, SciPy, Matplotlib, and Seaborn for data manipulation, statistical analysis, and visualisation. Familiarity with Monte Carlo simulations in Python and/or PyMC3 for Bayesian modelling is a plus. More ❯