This position will be based in Whitehouse Station, NJ and support Chubb's Global Analytics unit within Personal Risk Services, North America.

Major Duties & Responsibilities

* Develop robust predictive models to enhance our pricing and underwriting capabilities, among other applications (e.g. operational efficiency, marketing, etc), with the goal of improving profitability.
* Thoughtfully identify and construct predictive variables from both internal and external data sources. Lead efforts to solve data challenges and improve variable performance.
* Work closely with product management during model builds to inject business insights into variable and model design, as well as interpret model results, in order to ensure we're building best in class models and ones that will be bought into by business partners.
* Identify and communicate key findings to product management and other business partners via presentations and written communications.
* Create and maintain documentation associated with the programs and models developed in order to facilitate training of other staff members and keep records of the decision making process.
* Provide support to the Model Implementation team on topics related to model development, including assistance with regulatory requests and documentation of pertinent data issues.
* Assist in the development of junior staff members by providing necessary training and acting as a resource for their inquiries.

Minimum Requirements

* If the candidate's background is in Actuarial, the candidate should have at least five years of related experience, at least five actuarial exams (ACAS preferred), and should have a strong grasp of advanced actuarial techniques. If background is in statistical modeling, at least five years of experience in building predictive models in support of specific business initiatives; graduate degree in related field preferred.
* A basic understanding of regression modeling and/or a strong interest in statistical modeling, data mining, and other related fields is required.
* Practical experience using statistical techniques and building predictive models is considered a plus, but not mandatory.
* Experience in personal lines is considered a plus, but not mandatory.
* Strong programming skills, preferably in a statistical software package (e.g., SAS, SQL, R, Python), is a significant plus.
* Ability to work productively on an interdisciplinary team through highly technical projects, as well as establish strong relationships and credibility with business partners.
* Excellent oral and written communication skills, as well as time management skills to meet scheduled due dates.

Chubb offers a competitive compensation package and comprehensive benefits package including life, health and dental, vision, a generous retirement savings plan, disability coverage, stock purchase plan, flexible spending accounts, tuition reimbursement, and business casual dress. At Chubb, we are committed to equal employment opportunity and compliance with all laws and regulations pertaining to it. Our policy is to provide employment, training, compensation, promotion, and other conditions or opportunities of employment, without regard to race, color, religion, age, sex, sexual orientation, transgender, national origin, disability, genetic information, veteran or marital status, or any other characteristic protected by law.

Chubb strives to offer a diverse and inclusive and rewarding work environment. Teamwork and mutual respect are central to how Chubb operates and we believe the best solutions draw upon diverse perspectives, experiences and skills. We operate in such a way where everyone, regardless of their singular background has the opportunity to contribute to our collective success.


Associated topics: actuarial assistant, analyst, cost, investment actuary, life actuary, mathmatics, model, probability, risk, statistics

* The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.

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