Director, Data Science

Pay Philosophy

The typical starting salary range for this role is determined by a number of factors including skills, experience, education, certifications and location. The full salary range for this role reflects the competitive labor market value for all employees in these positions across the national market and provides an opportunity to progress as employees grow and develop within the role. Some roles at Liberty Mutual have a corresponding compensation plan which may include commission and/or bonus earnings at rates that vary based on multiple factors set forth in the compensation plan for the role.

Description

The Auto Product Design & Modeling team has an opening for Director II, Data Science position leading the Auto Underwriting & Fraud Modeling team. Underwriting models are a high profile and exciting area where we are able to apply creative problem-solving skills to have a considerable impact on business results. This role will lead a team of 4-6 data scientists in building predictive models to ensure a strong Personal Lines Auto portfolio. 

 

This manager will have an opportunity to work with highly talented professionals developing solutions to complex problems and delivering predictive tools and insights, including ongoing monitoring of metrics and initiatives. Integral to this position is creative problem solving and a mindset of viewing everything as possible, while creating an environment that excites and motivates the team. The ideal candidate is resilient (undeterred by setbacks), passionately driven to make things better, holds themselves to a high standard and wants to be surrounded by others who do the same.

 

**This role may have in-office requirements based on candidate location.**

 

Responsibilities:

• Build and develop a team of best-in-class modelers
• Own the accuracy and effectiveness of our Auto Underwriting & Fraud models
• Establish yourself as a self-driven leader, providing both strategic and tactical direction in the US Personal Lines Auto space
• Develop and implement a modeling strategy for comprehensive UW programs across the policy life cycle, as part of the holistic auto strategy (UW, Pricing, Telematics)
• Provide expert insights and data-driven recommendations to inform product design decisions in collaboration with internal stakeholders, and communicate vision to senior leaders
• Explore and utilize advanced modeling techniques
• Build strong relationships with leaders across the organization to maximize the impact of our Underwriting programs

Preferred Qualifications:

• Proven math and analytical skills, as typically acquired through the pursuit of an FCAS or advanced degree in Mathematics, Statistics, Economics, Actuarial Science or related field.
• Strong analytical skills with solid understanding of casualty insurance techniques, standards, and assumptions. Expert skills in statistical software packages (e.g., Emblem, Python packages) highly desired.
• Strong knowledge of insurance principles, underwriting and ratemaking concepts
• High-level knowledge of data sources, tools, and the business (lines, systems, pricing plans), predictive modeling (GLMs, GBMs, Elastic Nets), and code (e.g. Python, R, SQL) preferred.

Qualifications

• Deep knowledge of predictive analytic techniques and statistical diagnostics of models.• Expert knowledge of predictive toolset, to include highly technical tools.• Proven ability to lead and drive projects and assignments to completion through others, to include prior experience effectively managing talent.• Demonstrated ability to exchange ideas and convey complex information clearly and concisely, verbally, visually (presentations and exhibits), and in writing, consistent with the audiences and stakeholders with which s/he interacts.• Ability to establish and build relationships within and outside the aligned functional area or SBU. Ability to give effective training and presentations to management and other groups.• Presents to senior or functional department leaders or executives.• Broad knowledge of business drivers and market context.• Has a value driven perspective with regard to understanding of work context and impact.• Competencies typically acquired through an advanced degree (in Statistics, Mathematics, Data Science or other relevant field of study) and 5 to 7 years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) with 10 years of relevant experience.• Insurance or financial services industry experience preferred.

About Us

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