14 of 14 Seaborn Jobs in the UK

R , and frameworks such as TensorFlow, PyTorch, scikit-learn, NumPy, pandas . Experience in data wrangling , data preprocessing , and statistical modelling. Skilled in data visualisation tools (e.g., Matplotlib, Seaborn, Tableau). Ability to work independently and lead projects from inception to deployment. Experience with big data technologies (Hadoop, Spark) and cloud platforms (AWS, Azure, GCP) - Desirable. If you More ❯

R , and frameworks such as TensorFlow, PyTorch, scikit-learn, NumPy, pandas . Experience in data wrangling , data preprocessing , and statistical modelling. Skilled in data visualisation tools (e.g., Matplotlib, Seaborn, Tableau). Ability to work independently and lead projects from inception to deployment. Experience with big data technologies (Hadoop, Spark) and cloud platforms (AWS, Azure, GCP) - Desirable. If you More ❯

. Proficiency in building data pipelines, ETL workflows, and collaborating with data engineers for scalable data solutions. Expertise in data visualization and storytelling using Tableau, Power BI, Matplotlib, Seaborn, or Plotly to present insights effectively. Strong knowledge of MLOps practices, including CI/CD pipelines, model deployment, monitoring, and lifecycle management. Ability to engage with business stakeholders, gather More ❯

learn, TensorFlow, or PyTorch . Solid understanding of statistics, predictive modeling, and data mining techniques. Experience with data visualization tools such as Tableau, Power BI, or matplotlib/seaborn . Familiarity with cloud platforms (AWS, Azure, GCP) is a plus. Strong problem-solving, analytical, and communication skills. Preferred Qualifications MSc or PhD in Computer Science, Statistics, Mathematics, or More ❯

recently completed) B.Tech/BE/M.Tech/MSc in Data Science, Computer Science, Statistics, or related fields Proficiency in Python + core libraries (Pandas, NumPy, Matplotlib/Seaborn, Scikit-learn) Familiarity with SQL for querying relational datasets Sound understanding of ML fundamentals – supervised/unsupervised learning methods Strong statistics foundation – distributions, hypothesis testing, probability Ability to interpret More ❯

recently completed) B.Tech/BE/M.Tech/MSc in Data Science, Computer Science, Statistics, or related fields Proficiency in Python + core libraries (Pandas, NumPy, Matplotlib/Seaborn, Scikit-learn) Familiarity with SQL for querying relational datasets Sound understanding of ML fundamentals – supervised/unsupervised learning methods Strong statistics foundation – distributions, hypothesis testing, probability Ability to interpret More ❯

probability, statistics, and linear algebra, with the ability to apply these concepts to real-world problems. Extensive proficiency in Python, including mastery of libraries like scikit-learn, pandas, seaborn, and matplotlib. Significant experience writing and optimising complex SQL queries for data retrieval and manipulation in large-scale databases. Strong experience of Azure Data Stack (Databricks/Data Factory More ❯

probability, statistics, and linear algebra, with the ability to apply these concepts to real-world problems. Extensive proficiency in Python, including mastery of libraries like scikit-learn, pandas, seaborn, and matplotlib. Significant experience writing and optimising complex SQL queries for data retrieval and manipulation in large-scale databases. Strong experience of Azure Data Stack (Databricks/Data Factory More ❯

probability, statistics, and linear algebra, with the ability to apply these concepts to real-world problems. Extensive proficiency in Python, including mastery of libraries like scikit-learn, pandas, seaborn, and matplotlib. Significant experience writing and optimising complex SQL queries for data retrieval and manipulation in large-scale databases. Strong experience of Azure Data Stack (Databricks/Data Factory More ❯

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 data More ❯

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 data More ❯

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 data More ❯

data access, documentation, and reproducibility. Desired Skills/Experience 4+ years of experience in data analytics or data engineering. High proficiency in Python (e.g., pandas, NumPy, matplotlib/seaborn) and SQL essential. Hands-on experience with BI tools (ideally Power BI) advantageous Familiarity with cloud-based data platforms (ideally Azure) advantageous. Strong problem-solving skills and attention to More ❯

Data ScientistHybrid Working - Local Site - 1-2 days a week on site.Financial ServicesLorien's leading banking client is looking for a number of Data Scientists to join them on a new long term project which will be working on GenAI More ❯