Director I, 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

As a Scientific Director within the Enterprise Data & Data Science (ED&DS) team, you will collaborate with a group of data science (DS) and machine learning engineering (MLE) experts to address Liberty's most complex data science challenges across the organization.

 

The ED&DS Science team was established to offer centralized support and expertise to data science teams across our global organization. Our projects target key areas that are of interest to multiple teams, aiming to uncover enterprise capabilities. These areas include cutting-edge research and experimentation in applying generative AI and other advanced technologies, the development of common tools and platforms, leadership of inner-source DS tooling, setting standards for delivering and measuring the quality of data science work, and spearheading the experimentation and adoption of new tools and techniques. We work on some of the most exciting projects throughout Liberty. If you're a data scientist with a leadership mindset, eager to make an impact through collaboration, someone who constantly asks, "How can we improve?" and wants to influence the culture of a Fortune 100 company, then ED&DS is the ideal place for you!

 

As a centralized group, our project scope is vast. Possible projects include: 

Establish criteria and identify/build tools to evaluate the quality of content produced by GenAI across various enterprise use cases.

Create prototype and MVP solutions to leverage Generative and other AI techniques to empower multiple teams and to push the edge of the possible.

Partner with technology and data science teams to identify, document, and advocate for cutting-edge data science capabilities, best practices, and tools at LMG, with a particular emphasis on advancements in the GenAI field.

Partner with technology teams to streamline, automate, and accelerate DS jobs-to-be-done across the enterprise, and refine our technical vision and strategy across our Data Science platforms

 

Responsibilities:

• Act as DS SME and be responsible for setting the various levels of scientific strategies for many of our initiatives.
• Create prototypes and MVP solutions to leverage Generative and other AI techniques to empower multiple teams and to push the edge of the possible.
• Identify tools and best practices for key elements of DS lifecycle, both traditional DS and GenAI, possible directions
• Working cross-org (and cross-functionally) to implement and scale solutions with focus on execution through others.
• Work with product owners, scientists and engineers of varying levels of expertise, and influence solutions across the Enterprise

Qualifications

• Broad knowledge of predictive analytic techniques and statistical diagnostics of models.
• Advanced knowledge of predictive toolset; reflects as expert resource for tool development.
• Demonstrated ability to exchange ideas and convey complex information clearly and concisely.
• Ability to establish and build relationships within and outside the organization.
• Ability to give effective training and presentations to management and other groups.
• Ability to use results of analysis to persuade team, department management or senior management to a particular course of action.
• 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 a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and a minimum of 3 years of relevant experience, a Master`s degree (scientific field of study) and a minimum of  6 years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) and a minimum of  8 years of relevant experience.
• GEN AI and ML expertise strongly preferred.

About Us

As a purpose-driven organization, Liberty Mutual is committed to fostering an environment where employees from all backgrounds can build long and meaningful careers. Through strong relationships, comprehensive benefits and c