Data Scientist

Job Responsibilities

• Lead the design and development of analytical solutions to deliver enhanced customer experiences, creating personalised data driven experiences for our customers at customer interaction.
• Collaborate with the Data Engineering team to ensure the data architecture and platform is in place to develop solutions for the data science consumers.
• Work closely with the Head of Data Insights and other key stakeholders and subject matter experts on the definition, design and implementation of these analytics and personalised solutions.
• Work with Head of Data Insights to create processes to measure the value of modelling to the organisation with clear targets, KPIs and measurement in place.
• Lead and Mentor junior Data Scientists. Be a lead in the organisation for data modelling and machine learning and lead by example with industry experience and best practice.
• Lead on the development and implementation of a Data Science and Data Visualisation platform to enable production strength modelling techniques.
• Build relationships with divisional I.T. and Data teams to work collaboratively on cross-divisional solutions.
• Manage and administer the Data and analytical systems as required.

Experience Required

• At least 5 years of experience leading a Data Science/Analytics team.
• Proven experience delivering analytics solutions in propensity modelling, cross-sell modelling, recommender systems and next best action.
• Skilled in use of statistical analysis, predictive analytics, clustering and machine learning to deliver actionable insights for the organisation.
• Deep experience of technologies used for data manipulation, statistical analysis and data visualisation – (SQL, Python, R and Power BI/Tableau)
• Excellent communication skills and demonstrable experience in working with teams across business and technical functions to deliver solutions that drive value as measured against the core KPI’s within the business.
• Proven experience in delivering solutions in the area of Customer Analytics and engagement.

• Experience in working in a cloud-based environment such as Azure, AWS or GCP.
• Financial Services experience is desirable.
• Knowledge of visualisation tools such as Power BI, Tableau.
• Strong proclivity for automation and DevOps practices.