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Job purpose
To leverage data science to drive the strategic direction of our data-driven initiatives, enhancing decision-making and operational efficiency. The role focuses on applying machine learning, statistical analysis, and data mining techniques to predict, classify, and uncover insights from the organisations data.
Main Duties:
Innovation: Work with the wider organisation toidentify opportunities for the use of data science techniques to support business processes, maximise insight and drive benefits realisation.
Data Visualisation and Communication: Create and present clear visualisations to convey complex data insights to non-technical stakeholders. Utilise storytelling to make data accessible and actionable
Collaboration with Digital, Data, and Technology Teams: Work closely with Data Engineers and other IT professionals to ensure data quality and accessibility. Collaborate on the integration of AI and machine learning technologies into systems and processes.
Innovation and Continuous Learning: Keep abreast of the latest data science trends and technologies. Experiment with new tools and techniques to enhance analytical capabilities.
Stakeholder Engagement: Engage with internal and external stakeholders to understand business needs and deliver data-driven solutions. Act as a subject matter expert in data science, confidently sharing knowledge and highlighting the potential opportunities and limitations.
Decision Support: Use data to support strategic and operational decision-making processes, including providing recommendations based on predictive modelling and analysis.
Ethical Oversight: Scrutinise data sources and algorithms for bias, ensuring privacy and compliance with data protection laws, and promoting transparency and fairness in all data science activities.
Essential experience
Technical Proficiency: Strong skills in programming languages like Python or R, and tools such as SQL, TensorFlow, or PyTorch.
Strong Analytical and Problem-Solving Skills: Ability to translate complex data into actionable insights. Creative in finding solutions to data challenges.
Effective Communication: Skilled in presenting complex data insights in a clear, concise manner to a non-technical audience.
Team Collaboration: Demonstrated ability to work effectively in multidisciplinary teams.
Adaptability and Continuous Improvement: Open to learning and adapting to new technologies and methodologies. Commitment to personal development and fostering a learning culture within the team
Methodical Approach: Ability to approach complex data projects with a systematic and organised methodology, ensuring accuracy and efficiency
A practical knowledge of data science tools and techniques, such as machine learning and natural language processing, and how to apply them at an operational level.
A strong understanding of the mathematical principles underlying machine learning algorithms
Awareness of data privacy, security, and ethical considerations in data science work.
Familiarity of the Microsoft ML stack, MLOps and Git would be beneficial.
Knowledge of research and relevant research methodologies to produce meaningful insight, particularly in a public sector setting
Educated to degree level or with equivalent relevant professional experience
