Manager, Data Science

The Innovation Lab The Strategic Analytics Innovation Lab (SAIL) is part of the global Strategic Analytics team and based in Singapore. The lab will: Act as a 'centre of excellence' for data science / analytics research initiatives (e.g. predictive underwriting, data mining, machine learning-enabled analysis. Deliver innovative solutions for the life insurance market, including underwriting rules engine design, portfolio risk management, product pricing and development, and sales processes. Act as a global 'co-hub' for data science initiatives along with the Strategic Analytics team based in London, but with greater focus on Asia/Australia market initiatives, Encourage the adoption and upskilling of Singapore-based pricing and research staff through training and exposure to data science projects, and allow PLRe to attract and cultivate new talent within Singapore, Allow better co-ordination between PLRe's research and analytics resources located in Europe, Toronto, Asia, and Australia given geography / timezones. The Role Given that the Innovation Lab will act as a 'co-hub' for Strategic Analytics divisionally, the role will help to undertake the collection, validation, and analysis of Pacific Life Re's unique insurance data sources across offices globally, and work with the existing Strategic Analytics personnel based in London and Australia. The role will be responsible for delivering projects for APAC and the global markets Pacific Life Re operate in, developing innovative insurance solutions utilising insights derived from predictive analytics.The role will work closely with a variety of teams within Pacific Life Re and our subsidiary insurtech company UnderwriteMe, including R&D, Pricing, Underwriting, and Sales & Marketing. Given the nature of the role, engagement with third parties (e.g. academic institutions, clients, industry groups) will also be necessary to build partnerships and explore new sources of data and opportunities to innovate.Duties Work on and lead targeted predictive analytics and projects for Pacific Life Re and UnderwriteMe clients - collaborating with clients and internal stakeholders on projects or research with innovative data utilisation and predictive modelling aspects, Support the integration of data science techniques and insights derived from projects into broader R&D, including projects that link to developing cutting edge Terms of Trade and capital risk assumptions, Support product development efforts related to the above, Work with third parties and clients to identify and integrate new data sources which could improve risk and product propositions, Actively participate in research-related initiatives, sharing expertise at industry and PLRe events, and to lead analytics projects in conjunction with direct insurance companies and other partners, Help to upskill other APAC teams by conducting training and knowledge sharing related to predictive analytics and data science Qualifications & Experience Bachelor degrees in statistics, computer science, mathematics, Actuarial Science, or related disciplines Strong mathematical background and experience relevant to developing statistical and machine learning models, including the associated data preparations and data visualisations Strong knowledge and experience in associated relevant tools (Python/R, SQL, Tableau, etc) Minimum 7 years' experience working in life insurance in either a similar role or in an R&D, pricing, or experience analysis capacity. Previous experience conducting analytics projects within the broader insurance and reinsurance market Working knowledge of the products and markets Pacific Life Re operates in - including product terms, pricing approaches, underwriting, and distribution Experience with AWS or other cloud-based infrastructure & tools Sufficient data engineering and computer science knowledge to manage data science projects end-to-end and help provide steer for related data management and IT infrastructure Ability to work independently and in collaboration with a wide variety of stakeholders with differing technical backgrounds Strong communication and presentation skills, particularly in explaining complex issues in clear terms, Good organisational and project management skills, and the ability to manage multiple projects and various stakeholders simultaneously Strong mentoring skills to develop and train junior members of the team Enthusiastic, with a keen drive and focus