Assistant Director, Data Science, Modeling Sophistication at Liberty Mutual Insurance

Boston, Massachusetts, United States -

Full Time

Start Date

Immediate

Expiry Date

23 Dec, 25

Salary

0.0

Posted On

24 Sep, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Deep Learning, Computer Vision, Machine Learning, Statistics, Experimental Design, Model Evaluation, Python, MLOps, Git, PyTorch, TensorFlow, Docker, Kubernetes, Multimodal Learning, Data Pipelines, Model Optimization

Industry

Insurance

Description

Description At Liberty Mutual, the Insights & Solutions group uses data, analytics, and technology to deliver innovative solutions that drive our US Retail Markets business forward. Within it, the Modeling Sophistication, Deep Learning Research team applies cutting-edge computer vision and deep learning to reimagine how we assess risk, design products, and serve customers. With a culture of rigor, reproducibility, and innovation, we turn complex images and high-dimensional data into actionable insights that power smarter decisions and drive real impact in insurance. As a Data Scientist, you will work with a multidisciplinary team of researchers and engineers to design, develop, and deploy computer vision and deep learning models. You will be responsible for translating research prototypes into production-ready solutions that deliver measurable business value. In addition to model development, you will contribute to methodological advancements, scalable data infrastructure, and cross-team scientific collaboration. **This role may have in-office requirements based on candidate location** **Level of position offered will be based on skills and experience at manager discretion** Responsibilities: Design, train, and deploy computer vision and deep learning models, from research and experimentation through production implementation. Collaborate with business stakeholders to deliver data products such as feature pipelines, predictive models, dashboards, and datasets derived from image data. Develop and maintain scalable data pipelines and model workflows, applying MLOps best practices for reproducibility, deployment, and monitoring. Research and prototype new methodologies for training, evaluating, and improving deep learning models, particularly for computer vision. Integrate model outputs into business applications and partner with engineering teams to operationalize models in production environments. Contribute to the design, construction, and validation of large and complex datasets in collaboration with cross-functional science teams. Communicate findings through technical presentations, reports, and recommendations to both technical and non-technical stakeholders. Participate in cross-functional working groups and contribute to the broader data science community to promote best practices. Preferred Skills & Experience: Demonstrated expertise in deep learning with an emphasis on computer vision. Strong foundation in machine learning, statistics, experimental design, and model evaluation metrics. Proficiency in Python and MLOps practices, with experience in version control (Git), code review, collaborative development workflows (e.g., GitHub/GitLab), and model versioning/experiment tracking (e.g., MLflow). Proficiency in deep learning frameworks such as PyTorch (preferred) or TensorFlow, with experience in model design, training, and deployment. Experience building and managing pipelines with workflow orchestration tools (e.g., Airflow, Luigi). Experience with Docker and CI/CD pipelines. Experience with container orchestration systems such as Kubernetes. Understanding of GPU acceleration, distributed training, and model optimization techniques (e.g., mixed precision, pruning, quantization). Experience with multimodal learning, including vision-language models and cross-modal representation learning. Track record of advancing research projects from ideation to implementation. Qualifications Broad knowledge of predictive analytic techniques and statistical diagnostics of models. Expert knowledge of predictive toolset; reflects as expert resource for tool development. Demonstrated ability to exchange ideas and convey complex information clearly and concisely. Networks with key contacts outside own area of expertise. Ability to establish and build relationships within the aligned functional area or SBU. Ability to give effective training and presentations to peers, management and less senior business leaders. Ability to use results of analysis to persuade team or department management to a particular course of action. 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 2 years of relevant experience, a Master`s degree (scientific field of study) and a minimum of 4 years of relevant experience or may be acquired through a Bachelor`s degree(scientific field of study) and a minimum of 5+ years of relevant experience. 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. 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 dedicated to fostering an inclusive environment where employees from all backgrounds can build long and meaningful careers. By actively seeking employee feedback and amplifying the voices of our seven Employee Resource Groups (ERGs), which are open to all, we create an environment where every individual can make a meaningful impact so we continue to meet the evolving needs of our customers. 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 California Los Angeles Incorporated Los Angeles Unincorporated Philadelphia San Francisco

Responsibilities

Design, train, and deploy computer vision and deep learning models while collaborating with business stakeholders to deliver data products. Contribute to methodological advancements and scalable data infrastructure.