Job Description
Job Category
Data Science
Typical Starting Salary
180,000-239,000
Minimum Salary
$152,900.00
Maximum Salary
$267,600.00
Schedule
Full-Time
Flexible Time Off Annual Accrual - days
25
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
How do we maximize the value of our research and development teams, get to market quicker, create safeguards to address increasing AI scrutiny, and work together to bring the entire enterprise to bear on our most challenging problems?
You are the kind of data scientist who wants to help an entire enterprise succeed. You want to help create tools and techniques that make our models more reliable. You create best practices to help DS get to market quickly. You find ways of measuring talent and tech debt, and you are excited to build a culture around continuous improvement with your colleagues. You inspire others to do their best, and to do better. You don’t just see a problem in code – you are excited to learn from it, to create a review process to prevent it, and to build a tool to automate the problem away in the future.
We are the Office of Enterprise Data and Data Science at Liberty Mutual, a central group whose mandate is to make it easy for our DS talent to excel across all markets. We help build advanced AI solutions, create a culture of learning and collaboration, and curate an ecosystem of tools used by all of our scientists. We work cross-functionally with business leads, compliance, and platform developers to tackle new problems that cross traditional market divides. If you want to be at the center of an enterprise whose life blood is predictive analytics and machine learning, and you strive to make things better – join us.
Responsibilities
- Broadly set vision and act as technical/scientific advisor for how to improve our Enterprise DS practice, via a combination of development programs, risk management processes, community culture, streamlining best practices, and similar initiatives.
- In partnership with Enterprise Risk Management, Global Compliance, and key DS leaders, create and streamline a Model Risk Management program to identify our current AI footprint.
- Help align research and governance initiatives for Generative AI and other next-generation tech, and create programs to ensure we experiment with integrity and speed.
- Help define and measure technical capabilities such as Machine Learning Operations (MLOps), High Performance Engineering, etc., and create programs and practices to drive adoption of best practices.
- Help collect, curate, and refine best scientific practices across the enterprise, establishing common documentation, knowledge sharing programs, training curricula, and development programs.
- Create and maintain a culture of continuous learning and collaboration across DS teams.
- In partnership with our Data Offices and Legal counsel, help drive strategy for advanced privacy protection using novel technologies, including Privacy Preserving Analytics, Synthetic Data, Federated Learning, Multiparty Communication, and other techniques to help us better protect our customers’ data while driving powerful insights.
- Work with business units across Liberty to educate DS, executives, and business users on ethical considerations around AI, including proper usage of AI, algorithmic bias, and risk management.
Qualifications
- Broad experience with hands-on modelling and DS lifecycle activities, particularly in Python, and ability to communicate at a high level with DS and non-technical leaders
- Demonstrated ability to build trust with stakeholders
- Demonstrated experience leading DS projects
- Proven ability to lead and drive high profile cross-functional projects and teams
- Broad understanding of emerging scientific trends and techniques in MLOps, privacy, interpretability, explainability, risk management, bias and fairness, hallucinations, etc.
- Competencies typically acquired through an advanced degree (in Statistics, Mathematics, Data Science or other relevant field of study) and 8 years of relevant experience or may be acquired through a Bachelor’s degree (scientific field of study) and 10 years of relevant experience.
About Us
At Liberty Mutual, our purpose is to help people embrace today and confidently pursue tomorrow. That's why we provide an environment focused on openness, inclusion, trust and respect. Here, you'll discover our expansive range of roles, and a workplace where we aim to help turn your passion into a rewarding profession.
Liberty Mutual has proudly been recognized as a "Great Place to Work" by Great Place to Work® US for the past several years. We were also selected as one of the "100 Best Places to Work in IT" on IDG's Insider Pro and Computerworld's 2020 list. For many years running, we have been named by Forbes as one of America's Best Employers for Women and one of America's Best Employers for New Graduates as well as one of America's Best Employers for Diversity. To learn more about our commitment to diversity and inclusion please visit: https://jobs.libertymutualgroup.com/diversity-inclusion
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