Senior Analyst II - Actuarial Pricing

The Purpose of the role

As a key member of the Actuarial Pricing team, he/she will be at the forefront of developing new innovative solutions with appropriate use of machine learning algorithms to prepare pricing models and solve business problems. 

This role uses machine learning techniques to solve challenging business problems, working in an intellectually strong group of actuaries and data scientists, and liaising with the various divisions of the company. The individual is expected to possess strong statistical knowledge, insurance pricing experience and outstanding understanding of machine learning methods.

Ideal candidate for this role is someone with a strong education in data science and experience in insurance pricing, and who is eager to tackle problems with innovative thinking without compromising detailed business nuances. One must be adept at solving diverse problems by utilizing a variety of different tools, strategies, machine learning techniques, and algorithms. The individual will be expected to interpret and communicate results with stakeholders in an effective manner.

 Responsibilities

• Loss cost modelling and building raters for digital products
• Work with stakeholders to define the scope of the project, determine analyses to be performed, manage deliverables against timelines, present of results and implement the model
• Develop models that help with solving the problem at hand
• Stay abreast of the developments in the rapidly changing field of machine learning
• Handle stakeholder requests and perform work with little to no assistance
• Gain deeper understanding of Chubb’s business and various products

Required knowledge, Skills and qualifications

• At least 2 years of work experience in insurance pricing
• Sound understanding of ML concepts – Probabilistic Models, Supervised vs Unsupervised Learning, Ensemble Techniques and Hyperparameter Optimization; Strong experience in developing machine learning models.
• 1-5 years programming experience in Python, including Numpy, Scipy, Pandas, Matplotlib and other machine learning libraries (or equivalent platforms)
• Able to work in a team setting to understand problems and map out solutions; Having strong problem solving skills
• Adept at research and looking to apply new methodologies
• Strong communication and presentation skills
• An advanced degree in data science, business analytics, computer science, statistics, mathematics or economics