Graduate Actuarial Analyst (Machine Learning)
- Posted 2025年04月22日 13:00
- Salary £30000 - £35000 per annum
- LocationLondon
- Discipline 精算与风险
- Reference22042025
Job description
We are proud to be exclusively partnering with a boutique consultancy firm specialising in actuarial modelling and advanced analytics. As they continue to grow, they are seeking a bright and ambitious Graduate Actuarial Analyst with a passion for machine learning to join their dynamic team.
This is a rare opportunity to join a high-calibre consultancy where you'll work closely with senior leadership, gaining hands-on experience on a range of cutting-edge projects across insurance, risk, and data science.
About the Role:
Apply machine learning techniques to complex actuarial problems, enhancing traditional actuarial models.
Work on real-world client projects across a variety of sectors.
Build bespoke models and predictive analytics tools.
Collaborate with a team of actuaries, data scientists, and consultants on innovative solutions.
Support actuarial modelling and reporting, with a strong data-driven and technical focus.
About You:
Recently graduated (or graduating) with a strong degree (2:1 or above) in a quantitative discipline (Mathematics, Statistics, Actuarial Science, Data Science, Engineering, or similar) from a top-tier university.
Achieved A or A* in Mathematics at A-Level (or equivalent).
Demonstrated experience with machine learning techniques, ideally through academic projects, internships, or personal projects.
Proficient with Python, R, or similar analytical languages.
Strong problem-solving and analytical thinking skills.
Excellent communication skills - comfortable presenting technical results to non-technical audiences.
Highly motivated, detail-oriented, and eager to learn in a fast-paced environment.
What's on Offer:
A unique chance to join a highly respected, growing consultancy at an early stage.
Fast-track development and progression with exposure to senior clients and cutting-edge projects.
Full actuarial study support (if pursuing exams) or support towards data science qualifications if preferred.
Hybrid working model with flexibility.
A collaborative, meritocratic culture where innovation and creativity are encouraged.
