Director I, Data Science at Liberty Mutual

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.

As a scientific Director in the Enterprise Data & Data Science (ED&DS), you will work in a team of data science (DS) and machine learning engineering (MLE) experts to collaborate across the enterprise and solve Liberty’s most challenging data science problems.

The ED&DS Science was created to provide centralized support and expertise to DS teams across the global organization. Our projects focus on key areas of interest to multiple teams in an effort to discover enterprise capabilities. These areas include: bleeding edge research and experimentation in generative and other forms of AI; common tool and platform development; establishing the standards of how to deliver and measure the quality of DS work; and leading experimentation and adoption of new tools and techniques. 

We work on some of the most exciting projects across all of Liberty. If you are the kind of DS that likes to ask, how can we do better? and impact the entire culture at a Fortune 100 company, this is the place for you!

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

1. Define metrics and assess quality of content generated by GenAI in the various use cases throughout the enteprise
2. Design and fine tune language models (NLP/NLU) to understand and build predictions or summaries from customer calls, claim notes, web chats, medical records, and beyond
3. Collaborate with technology partners to adopt, design, build, and/or integrate MLOps tools for the organization, ensuring they support broad DS needs, and help other DS groups adopt modern MLOps practices
4. Explore the advantages and limitations of privacy-preserving ML and synthetic data, to accelerate experimentation and better protect our customers’ data

Responsibilities:

• Develop and implement the scientific strategy for our initiatives, operating cross-organizationally and cross-functionally.
• Recognize new strategic opportunities for applying theoretical methods and tools.
• Use a comprehensive understanding of advanced Machine Learning (ML) techniques and programming skills to implement, scale, and advance solutions from Proof-of-Concept (PoC) to Minimum Viable Product (MVP) and beyond.
• Communicate and justify strategies and initiatives to business partners and other stakeholders using easily understandable visuals for non-technical audiences, offering a clear perspective for interpreting the data.
• Propel innovation in the creation and enhancement of tools and practices.
• Manage large components of highly complex projects.
• Advise on project design as a technical consultant for the team.
• Frequently engage with the data science community and lead cross-functional working groups.
• Collaborate with other scientists and engineers of various expertise levels, and influence solutions across the organization. If you enjoy a diverse range of responsibilities, along with significant exposure and impact within a large organization, this role is perfect for you!

• Broad knowledge of predictive analytic techniques and statistical diagnostics of models.
• Extensive experience in Python is required
• 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.
• Ability to work EST is required.

**This position may have in-office requirements depending on candidate location.**

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 continuous learning opportunities, we seek to create an environment where employees can succeed, both professionally and personally. 

At Liberty Mutual, we believe progress happens when people feel secure. By providing protection for the unexpected and delivering it with care, we help people embrace today and confidently pursue tomorrow.

We are proud to support a diverse, equitable and inclusive workplace, where all 45,000 employees feel a sense of community, belonging and can do their best work. Our seven Employee Resource Groups (ERGs) offer a centralized, open space to bring employees and allies together to connect, learn and engage.

We value your hard work, integrity and commitment to make things better, and we put people first by offering you benefits that support your life and well-being. To learn more about our benefit offerings please visit: https://LMI.co/Benefits

Liberty Mutual is an equal opportunity employer. We will not tolerate discrimination on the basis of race, color, national origin, sex, sexual orientation, gender identity, religion, age, disability, veteran's status, pregnancy, genetic information or on any basis prohibited by federal, state or local law.

Fair Chance Notices

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