Data Scientist with Python

This hybrid position is available in multiple locations — London, Edinburgh, Newcastle, and Erskine — with the expectation to attend any of these offices when required.

Project Description:

We are seeking a highly experienced Data Scientist with deep expertise in Python and advanced machine learning techniques. You need to have a strong background in statistical analysis, big data platforms, and cloud integration, and you will be responsible for designing and deploying scalable data science solutions.

Responsibilities:

• Develop and deploy machine learning, deep learning, and predictive models.
• Perform statistical analysis, data mining, and feature engineering on large datasets.
• Build and optimize data pipelines and ETL workflows.
• Collaborate with data engineers and business stakeholders to deliver actionable insights.
• Create compelling data visualizations using tools like Tableau, Power BI, Matplotlib, or Plotly.
• Implement MLOps practices, including CI/CD, model monitoring, and lifecycle management.
• Mentor junior data scientists and contribute to team knowledge-sharing.
• Stay current with trends in AI/ML and data science.

Mandatory Skills Description:

• Minimum 8+ years of hands-on experience in Data Science with strong expertise in Python and libraries such as Pandas, NumPy, SciPy, Scikit-learn, TensorFlow, or PyTorch.
• Proven ability to design, develop, and deploy machine learning, deep learning, and predictive models to solve complex business problems.
• Strong background in statistical analysis, data mining, and feature engineering for large-scale structured and unstructured datasets.
• Experience working with big data platforms (Spark, Hadoop) and integrating with cloud environments (AWS, Azure, GCP).
• 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 requirements, and deliver actionable insights aligned with business goals.
• Experience in mentoring junior data scientists/analysts, leading projects, and contributing to knowledge-sharing across teams.
• Continuous learner with strong problem-solving, communication, and leadership skills, staying updated with the latest trends in AI/ML and data science.