Head of Data Science / Lead Data Scientist

About the Role

The Head of Data Science / Lead Data Scientist will join a global Fintech / InsurTech company. This role requires a hands-on capacity in Lead Data Programming, Statistical / Data Modelling, combined with line management duties for a team of 3 Data Scientists. You will be instrumental in helping insurance product teams understand their data and drive output across multiple products.

Responsibilities

• Lead the data science team from a hands-on line management perspective.
• Be heavily involved throughout all parts of the data science project life cycle from design and architecture through programming and data engineering (data modelling, statistical data analytics, predictive analytics, ETL etc).
• Build predictive models and analytic solutions to support the underwriting function on a global basis.
• Engage with multiple stakeholders including underwriters, insurance product line managers and actuaries (pricing) to both identify profitable growth areas and optimize portfolio performance.
• Lead the extraction and manipulation of data using data management techniques and tools from both internal and external sources.
• Undertake text mining and data mining techniques.
• Perform statistical analysis and multivariate procedures using Data Science programming methods and tools including R, Python, SAS, SQL.
• Present findings to senior level stakeholders and then work to develop data models and solutions into production across multiple departments.
• Work with large data sets across multiple sources from within the business and its subsidiaries to develop advanced data analysis techniques and customised modelling solutions.
• Leverage Big Data from a data science perspective and feed these analytical capabilities into the ongoing development of systems for the business worldwide.

Requirements

• Demonstrable experience leading and managing a small team while remaining a hands-on Data Scientist.
• Comfortable with contemporary data science languages including R, Python, and SQL.
• In-depth knowledge of data modelling, predictive analytics, and multivariate procedures.
• Experience in text mining, machine learning, natural language processing, or AI is highly beneficial but non-essential.
• Comfortable engaging with senior level stakeholders and presenting to them to develop solutions.
• Experience gained within the Insurance / Reinsurance sector is highly desirable, but not essential; experience gained with Financial Services or related sectors is preferable.
• Degree level education is sought.
• Excellent communication skills are a pre-requisite.