Description**Candidates who live within 50 miles of Boston, MA; Portsmouth, NH; Seattle, WA; Columbus, OH; or Plano, TX will follow a hybrid schedule, coming into the office two days per week. Otherwise, this role is remote with occasional travel. **
As an Assistant Director you will:
• Apply knowledge of sophisticated analytics techniques to manipulate large structured and unstructured data sets to generate insights to inform business decisions.
• Lead end-to-end development of new predictive models for high-impact business outcomes (e.g., improving claims handling efficiency): frame and test hypotheses, design statistically rigorous experiments, assemble/label training data, engineer features, and train/validate models.
• Build state-of-the-art ML systems that leverage structured data, unstructured text, and generative AI.
• Select and implement appropriate algorithms and evaluation methods to deliver measurable accuracy and business value.
• Follow ML Ops best practices to create organized code repos, production-quality code, and reproducible results.
• Stay up-to-date with the latest advancements in data science and machine learning, and apply them to solving complex problems in the insurance claims domain.
• Provide technical mentorship and guidance to junior data scientists.
• Responsible for larger components of projects of moderate to high complexity.
• 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 and experience:
• Broad conceptual understanding and practical knowledge of the end-to-end data science lifecycle.
• Exceptional hands-on data science technical skills (e.g. SQL, Python, and Statistical Inference).
• Experience collaborating with non-technical stakeholders to understand which problems need solving, design solutions, and bring them to market.
• Experience working with complex Type II data to assemble training datasets to appropriately model operational processes.
• 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).
Additional skills and experiences that are nice to have:
• Knowledge of claims handling processes and experience working with claims data.
• Experience developing LLM-based solutions for production use cases.
• Practical experience with cloud platforms like AWS (preferably), Google Cloud, or Azure.
• Familiarity with data pipeline and workflow management tools like Airflow, among others.
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.
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.
