Assistant Director, Data Science (Stp)

Liberty Mutual Insurance; Seattle (WA); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Liberty Mutual Insurance is seeking a data science leader to deliver predictive analytics solutions across insurance use cases. You will define problems, prepare data, engineer features, build models, validate outcomes, and deploy solutions at scale.

You will translate business goals into analytic plans, collaborate with stakeholders, and apply ML, deep learning, and computer vision techniques to large datasets. Remote/hybrid work options are available with travel as needed.

Qualifications

• Experience conducting data-driven experiments to support business decisions in an insurance setting.
• Deliver strategic decision support using insurance analytics and pricing platforms (e.g., Emblem, Earnix).
• Implement data and model artifact versioning and reproducible ML workflows (DVC/MLflow).
• Build and maintain monitoring dashboards and production data pipelines (Snowflake/Airflow).
• Apply geospatial fundamentals (CRS, projections) and pixel-to-geo transforms.
• Train, evaluate, and improve computer vision models (object detection/segmentation).
• Optimize deep learning training performance via profiling and data loading.
• Develop, deploy, and operate data science solutions on AWS/Azure with CI/CD.

Responsibilities

• Lead end-to-end delivery of predictive analytics solutions, including problem definition, data preparation, feature engineering, model development, validation, and deployment.
• Translate business objectives into analytic approaches, success metrics, and project plans for medium-sized data science initiatives.
• Partner with cross-functional stakeholders to gather requirements and align analytics deliverables with business strategy.
• Apply ML, deep learning, statistical modeling, and optimization techniques to large structured and unstructured datasets to generate insights and predict outcomes.
• Identify and test hypotheses using appropriate statistical methods and evaluate model performance for rigor.
• Develop and apply computer vision methods for insurance use cases, including model training, evaluation, and monitoring.
• Produce clear visualizations and narratives that communicate findings to non-technical and senior audiences.
• Document modeling methodology, assumptions, limitations, and results for reproducibility and governance; monitor model performance over time.
• Provide technical guidance through code reviews and best-practice recommendations for team execution.
• Position requires domestic travel up to 10%; telecommuting permitted up to 60%.

Skills

Experimentation

Hypothesis testing

Communication of findings

Geospatial fundamentals

Computer vision

Deep learning

Model deployment

Cloud platforms

Education

PhD in Computer Science, Statistics, or related field

Master’s in Computer Science, Statistics, or related field

Tools

Emblem

Earnix

DVC

MLflow

Snowflake

Airflow

Docker

AWS

Azure

Job description

Description

Duties:

• Lead end-to-end delivery of predictive analytics solutions, including problem definition, data preparation, feature engineering, model development, validation, and deployment.
• Independently translate business objectives into analytic approaches, success metrics, and project plans for medium-sized data science initiatives.
• Partner with cross-functional stakeholders to gather requirements, prioritize use cases, and align analytics deliverables with business strategy.
• Apply machine learning, deep learning, statistical modeling, and optimization techniques to large structured and unstructured datasets to generate insights and predict outcomes.
• Identify and test hypotheses using appropriate statistical methods and evaluate model performance to ensure statistical rigor of findings.
• Develop and apply computer vision methods for insurance-domain use cases, including model training, evaluation, and monitoring.
• Produce clear visualizations and written/presented narratives that communicate findings and recommendations to non-technical and senior audiences.
• Document modeling methodology, assumptions, limitations, and results to support reproducibility and governance and implement monitoring to maintain model performance over time.
• Provide technical guidance through code review and best-practice recommendations to support team execution and consistency.
• Position requires domestic travel up to 10%.
• Telecommuting permitted up to 60%.

Qualifications

Requirements:

• Employer will accept a PhD degree in Computer Science, Statistics, or related field and two (2) years of experience in the job offered or in an Asst Dir, Data Science (STP)-related occupation.
• Alternatively, employer will accept a Master’s degree in Computer Science, Statistics, or related field and four (4) years of experience in the job offered or in an Asst Dir, Data Science (STP)-related occupation.
• Position requires demonstrable experience in the following:
• Conduct experiments and data-driven studies to support business decisions in an insurance setting, including hypothesis testing, interpreting results, and communicating findings.
• Deliver strategic decision support using insurance analytics and pricing platforms, including Emblem, Earnix, or equivalent tools.
• Implement data and model artifact versioning and reproducible ML workflows using version control tools, including DVC and MLflow.
• Build and maintain monitoring dashboards and production data pipelines using data warehouse and workflow orchestration tools, including Snowflake and Airflow.
• Apply geospatial fundamentals, including coordinate reference systems, map projections, and pixel-to-geo transforms.
• Train, evaluate, and improve computer vision models, including object detection and segmentation, and perform model performance diagnostics and error analysis.
• Optimize deep learning training performance through profiling, efficient data loading, and training optimizations.
• Develop, deploy, and operate data science solutions using public cloud platforms, including AWS and Azure.
• Containerize ML services and pipelines using Docker and apply CI/CD and deployment automation practices for production releases.
• Monitor and troubleshoot production scoring and data pipelines, including performance tracking, incident triage, and root-cause analysis.
• Develop and maintain labeling guidelines and label taxonomies for computer vision datasets, and coordinate with annotation resources to support dataset development.
• Experience may be gained during graduate program. Will accept any suitable combination of education, training, and/or experience. Multiple Positions Available.

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.

Fair Chance Notices

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