REINSURANCE ACTUARY, 30082
Aylesbury
You will be managing and mentoring junior members of the wider actuarial and pricing teams.
MANAGER, MEDICAL ANALYTICS R&D 30028
This is an exciting opportunity for a Manager with strong technical skills and experience in biometric risk modelling to join and build insured annuities business and invest in the analytics, modelling and assumption-setting capability needed to support future growth. With access to rich health and underwriting data, you will play a key role in developing the assumptions, models and insights that underpin individual and enhanced annuities propositions.
Ref: 30028
- Location: London
- Category: Life Actuarial
- Type: Permanent
Overview
Key responsibilities including but not limited to;
- You will support the Head of Medical Analytics with managing and conducting health-related analytical projects, with a core remit of supporting basis development, pricing and underwriting rules for UK individual and enhanced annuities products
- Responsibilities include planning, evidence synthesis, data sourcing, data analysis, model design, validation and results communication. As part of these projects, you will be transforming quantitative and qualitative analysis into assumptions and uplifts for use in the rest of the business
- Conducting analytical projects to support UK individual and enhanced annuities basis development
- Contributing to analytical projects in the Medical Analytics or wider R&D team
- Contribute to wider research initiatives such as thought leadership articles and building relationships with relevant health analytics networks
Qualifications required:
- Qualified Fellow of the Institute or Faculty of Actuaries or other similar actuarial organisation; or advanced qualification in a health-related subject (e.g. Masters/PhD in Epidemiology, Biostatistics, Health Data Science or Health Economics)
Experience required:
- Excellent organisational skills and able to coordinate the work of multi-disciplinary teams in fast-paced commercial settings
- Proficient in turning quantitative and qualitative insights into practical and actionable outcomes
- Experience in explaining complex technical or commercial issues to a variety of audiences, via written and spoken communication
- Knowledge of modelling techniques such as survival models, disease progression models, simulation models, intervention models and causal inference