Actuarial Data Product Owner

Actuarial Data Product Owner



The Actuarial Data Product Owner role is held by an experienced professional with significant, hands-on data ownership experience.  In addition to technical expertise, this role requires the ability effectively managing projects from end to end in a collaborative environment.  A key focus of this position will be to progress strategic initiatives that are mostly new areas of exploration for AAIS, including the pursuit of additional data sources, streamlining data flows, and developing/improving modeling capabilities. 

This position functions in an agile, collaborative, and cross-functional environment to development state of the industry advisory organization products. Core to this role is working with Actuaries, Data Engineers, Analysts, and Affiliates to innovate and deliver creative solutions to complex industry challenges.



  • Take leadership role in data discovery and evaluation to increase the volume and quality of insurance and non-insurance data available for analysis
  • Streamline the process to ingest data by improving data flows and developing appropriate quality checks/reports
  • Support actuarial automation initiatives to decrease processing time of actuarial analyses
  • Understand and communicate how modeling tools and techniques are used to analyze data, develop solutions for specific business problems, discover unasked questions/opportunities, and to better understand risk
  • Incorporate modeling results into actionable, sustainable solutions to business problems
  • Take leadership role in developing modeling capabilities suitable for use within the openIDL network
  • Manage data driven development projects under the leadership and strategic direction of the Chief Actuary or VP
  • Provide technical expertise and leadership in analyzing and visualizing large, complex, and unique data sets required to execute business initiatives
  • Manage multiple priorities in parallel and meet agreed upon deadlines by communicating and adjusting workload and expectations
  • Promote collaboration across teams to expand analytics touchpoints across the organization and broaden technical skills
  • Serve as application/system steward for data processing software, data catalog, and external data sources.  May also include geospatial applications, catastrophe models, and Risk Awareness Service


Skills, Knowledge and Abilities:

  • Entrepreneurial inclination to discover novel opportunities for applying analytical techniques to business problems across the insurance industry.
  • Ability to quickly become an expert on AAIS’s data and industry position and in-depth knowledge of Property and Casualty Insurance products and data.
  • Hands on experience working with large structured and unstructured data sets, including statistical analyses, predictive modeling, AI/Machine Learning and/or data visualization.  Proficiency with generalized linear models is preferred.
  • Problem Solving/Critical Thinking skills: making the best decisions possible given the data quality and time available.
  • Skills and/or ability to learn and understand additional tools that aid data driven analysis and actuarial work (e.g., SAS, SQL, catastrophe modeling software, etc.).
  • Excellent written and oral communication skills; must be capable of fully yet concisely articulating technical concepts to non-technical audiences.
  • Ability to make business recommendations based on data insights
  • Strong collaboration and mentoring skills.



  • BS in Mathematics, Actuarial Science or other data driven analysis related discipline.
  • 5+ years of experience in a data analytics development environment; insurance industry a plus, but not required
  • Strong skills in other data science related languages and tools are preferred (SQL, Git, SAS)
  • Significant expertise in a variety of analytical models and leveraging data to make business decisions.
  • Proficiency in the Microsoft Office Suite.
  • Experience in an agile development environment preferred
  • A record of success and top-tier achievement in prior work and education experiences.
  • Proficiency and significant experience using modeling software (RStudio, Python, SQL, others) to run modeling techniques such as generalized linear models, decision trees, clustering, etc. is preferred



Product Owner: Actuarial Applications:

  • Third-party tools and datasets relevant to actuarial analytics projects, such as ArcGIS tools, Spectrum, NFIRS dataset, Precisely datasets


Application & System Stewardship:

  • ArcGIS (Application & System)
  • Pitney-Bowes Spectrum (Application)
  • RStudio (Application & System)


Resumes to: