Director I, Data Science, Enterprise Data & Data Science

Remote from: USA
Annual salary: Undisclosed
Salary information is not provided for this position. Check our Salary Directory to estimate the average compensation for similar roles.
Department: Data Science & Analytics
Employment type: Full Time,
Job posted: 2 Jul 2026
Apply before: 2 Aug 2026
Experience level: Director
Views / Applies: 39 / 0

About company

About Liberty Mutual

At Liberty Mutual, we want to help you embrace today and confidently pursue tomorrow

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Actively Hiring

AI Summary

This Director-level role is for a hands-on Data Scientist with deep expertise in data science, MLOps, and generative AI. You will design and evaluate GenAI solutions, develop semantic data layers and knowledge graphs, and champion best practices across a large data science organization. The position requires strong collaboration with cross-functional teams and clear communication to non-technical stakeholders. It is an individual contributor role focusing on high-impact projects and technical innovation.

Role DNA

Job Complexity

Easy Hard

Pace & Pressure

Relaxed Fast-paced

Autonomy Level

Guided Full Ownership

Communication Load

Independent Highly Collaborative

AI Insight The role requires advanced expertise in multiple cutting-edge areas like GenAI, MLOps, and knowledge graphs, along with strong leadership and communication skills, making it highly challenging.

Salary Analysis

AI Insight Based on the national market for Director-level Data Science roles, the estimated median salary is $200,000. Since the job posting does not specify a salary range, this estimate aligns with typical compensation for a hands-on, senior individual contributor role with expertise in GenAI, MLOps, and enterprise data strategy.

Core Skills Required

Data Science Machine Learning MLOps Generative AI Knowledge Graphs Deep Learning Statistical Modeling Cross-functional Collaboration Enterprise Data Strategy Predictive Analytics

Cover Letter Sample

Dear Hiring Manager,

I am writing to express my strong interest in the Director I, Data Science position within the Enterprise Data & Data Science team. With a PhD in a scientific field and over 10 years of experience in data science and machine learning, I have a proven track record of building and deploying advanced AI solutions at scale. My expertise spans MLOps, generative AI, and knowledge graphs, aligning perfectly with the requirements of this role.

In my previous position, I led the development of GenAI evaluation frameworks that improved model reliability by 30% and established semantic data layers that enhanced data accessibility across the enterprise. I am passionate about fostering best practices and collaborating with cross-functional teams to drive innovation. I look forward to the opportunity to contribute to Liberty Mutual’s data science community and help shape the future of AI in insurance.

Sincerely,
[Your Name]

Sample Interview Questions

Can you describe your experience with building and deploying generative AI solutions in a large enterprise environment?

I have led the development of several GenAI solutions, including a chatbot for customer support that reduced response times by 40%. I implemented MLOps pipelines for continuous monitoring and retraining, and worked closely with legal and compliance teams to ensure safety and ethical use.

How do you ensure best practices in MLOps across a distributed data science team?

I advocate for standardized tooling and version control for data, models, and experiments. I also organize regular code reviews and knowledge-sharing sessions, and implement automated CI/CD pipelines for model deployment and testing.

Explain how you would design a semantic data layer to support data discovery.

I would start by identifying key business concepts and relationships, then build a knowledge graph using a graph database like Neo4j. I would integrate metadata from various data sources and provide a natural language query interface to enable business users to find relevant data quickly.

Describe a time you communicated complex technical findings to non-technical stakeholders effectively.

I presented a machine learning model's performance to marketing executives using real-world examples and visualizations, focusing on business impact metrics like increased conversion rates. I avoided jargon and explained limitations in simple terms, which helped them make an informed decision to deploy the model.

What is your approach to evaluating the performance and safety of generative AI models?

I use a combination of automated metrics (e.g., BLEU, ROUGE) and human evaluation for quality, along with adversarial testing for safety. I also implement guardrails to detect and filter harmful outputs, and conduct regular audits to ensure compliance with ethical guidelines.

Description

We’re seeking an exceptional, hands-on Data Scientist with deep expertise in data science, MLOps, and building GenAI solutions to join our Enterprise Data & Data Science team. In this role, you’ll identify, evaluate, and develop solutions at the intersection of data science, generative AI, and enterprise data strategy—including GenAI evaluation frameworks and semantic data layers. You’ll also serve as a community champion, driving the adoption of best practices across a large, collaborative data science organization.

Responsibilities:

Design, build, and evaluate generative AI solutions and agentic systems
Develop and maintain data semantic layers and knowledge graphs for enterprise-scale data accessibility
Build evaluation frameworks and tools to assess GenAI systems’ performance, reliability, and safety
Collaborate with other data scientists, machine learning engineers, data engineers, and business partners
Champion best practices and tooling across a broad data science community
Lead cross-functional working groups and contribute to innovation in AI/ML methods
Communicate complex technical findings clearly to non-technical stakeholders
Serve as a technical consultant on complex, high-impact projects
Please note this is an individual contributor role

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.

Preferred Experience:

Strong foundation in data science and machine learning
Proven MLOps expertise across the complete data science lifecycle
Experience building GenAI solutions and agentic systems
Familiarity with GenAI evaluation methodologies
Experience with data semantic layers and/or knowledge graphs
Track record of cross-functional collaboration in a large enterprise environment
Ability to work ET hours

About Us

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.
At Liberty Mutual, our goal is to create a workplace where everyone feels valued, supported, and can thrive. We build an environment that welcomes a wide range of perspectives and experiences, with inclusion embedded in every aspect of our culture and reflected in everyday interactions. This comes to life through comprehensive benefits, workplace flexibility, professional development opportunities, and a host of opportunities provided through our Employee Resource Groups. Each employee plays a role in creating our inclusive culture, which supports every individual to do their best work. Together, we cultivate a community where everyone can make a meaningful impact for our business, our customers, and the communities we serve.
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://www.libertymutualgroup.com/about-lm/careers/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.
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