Data Scientist

mthree is looking looking for a proactive and strongly motivated Data Scientist to join our dynamic and collaborative team for one of our client. The successful candidate will have the opportunity to work on a variety of innovation and change projects, contribute their own ideas to enable efficiencies and business value and collaborate with colleagues across. Specifically, this role will take the lead on anomaly detection processes across a range of regulatory and statistical datasets, using machine learning techniques to surface meaningful insights and improve data quality. They will also play a key role in the development and maintenance of interactive dashboards and visualisation tools that support decision-making and enhance transparency across.

An active SC clearance is required for this role

Role: Data Scientist

Location: London or Leeds

Role Requirements:

The job holder will need to have:

• Strong technical and quantitative skills.
• Demonstrable experience in identifying and implementing improvements in data processes through the use of automation, with experience of handling and manipulating large volumes of data in an efficient, effective and accurate way.
• Strong demonstrable experience of using programming languages (such as R, Python, and SQL) and advanced data manipulation techniques with an ability to understand their practical application in numerical analysis and data quality.
• Experience with using Machine Learning via home-grown models, and using off-the-shelf AI technologies such as Power Automate, Copilot, etc.
• Ability to communicate effectively, clearly, and confidently both orally and in writing.
• Commitment to promoting an innovative and inclusive team culture, with openness to experimentation, constructive challenge, and continuous learning.
• A high level of motivation and autonomy in their day-to-day work and when acquiring new skills and knowledge.

The job holder will need to have:

• A good understanding of economics, finance, and the UK regulatory and statistical datasets would be preferable though there is plenty of scope to build up expertise in these areas.
• Experience of building relationships with stakeholders.
• Experience developing and maintaining interactive dashboards (e.g. using Shiny, Plotly, Dash, Power BI, Tableau) for data quality monitoring and insights.
• Experience in designing and implementing data models, pipelines and complex coding solutions.
• Knowledge of using collaboration, version control and DevOps tools including but not limited to Jira, Confluence, Azure DevOps, Git is an added advantage.