Senior Principal Data Analyst

GEICO•Bethesda, MD

1d•$100,000 - $300,000

About The Position

Under minimal supervision, the Senior Principal Data Analyst develops and maintains robust data solutions, reporting frameworks, dashboards, and visualizations to drive business insights and support strategic decision-making. The role partners with business stakeholders, data engineers, architects, governance teams, and technology partners to translate business requirements into scalable analytical solutions. The position leads complex analytical initiatives; oversees data preparation and governance activities; develops reporting and modeling solutions; and identifies opportunities to improve business performance through data-driven decision-making. It supports business functions including Underwriting, Claims, Marketing, Advertising, and Product Management. The ideal candidate brings advanced analytical expertise, business acumen, project leadership skills, and the ability to communicate insights to technical and non-technical audiences. The analyst also leads cross-functional projects, provides technical guidance to junior analysts, improves processes, and supports production implementation of analytical models and business solutions.

Requirements

Bachelor's degree in Statistics, Mathematics, Data Science, Economics, Computer Science, Engineering, Operations Research, or a related quantitative field.
Master's degree or PhD in a quantitative discipline.
At least 9 years of analytical experience with a bachelor's degree, or at least 7 years with a master's degree.
Experience leading complex analytical projects and cross-functional initiatives.
Advanced SQL/SAS SQL proficiency.
Experience with cloud-based data platforms and databases.
Strong proficiency in R.
Advanced Microsoft Excel skills, including Pivot Tables, VLOOKUP/XLOOKUP, charts and data visualization, and complex formulas and analysis.
Experience creating analytical reports, dashboards, and data models.
Ability to apply statistical, mathematical, and data mining techniques to solve business problems.
Understanding of insurance products, rating methodologies, and insurance principles.
Strong ability to translate data insights into business recommendations.
Ability to work independently and collaboratively in a team environment.
Ability to manage multiple priorities and competing deadlines.
Ability to learn and apply complex technical, business, and operational concepts.
Strong written and verbal communication skills.
Ability to perform essential job functions with or without reasonable accommodation, including seeing, hearing, speaking, and using computer systems.

Nice To Haves

Experience working within insurance, financial services, or other highly data-driven environments.
Strong background supporting Claims, Underwriting, Marketing, Product Management, or Pricing.
Python programming experience.
Experience with business intelligence and visualization tools such as Power BI, Tableau, or similar.
Experience with machine learning and predictive analytics.
Familiarity with data governance and data quality frameworks.
Knowledge of Claims, Underwriting, Marketing, Agency Operations, or related insurance functions.
Experience with project management, process improvement, and operational analytics.

Responsibilities

Lead the design, development, and maintenance of data models, analytical solutions, reports, and dashboards.
Manage complex data extraction, transformation, and validation processes to ensure data quality and accuracy.
Serve as a subject matter expert across multiple business and data domains.
Translate business problems into analytical approaches and actionable recommendations.
Perform advanced statistical analysis, data mining, forecasting, and research to support business objectives.
Develop solutions to complex business challenges and improve operational performance.
Lead data exploration, proof-of-concept initiatives, and research into emerging analytical methodologies.
Oversee departmental data sources and ensure consistent application of data standards and governance practices.
Validate, reconcile, and monitor data sources for reasonableness, completeness, and accuracy.
Develop and maintain documentation, including data definitions, business rules, technical specifications, and analytical methodologies.
Identify, assess, and implement new data sources and technologies to improve analytics capabilities.
Partner with Data Governance and Technology teams on enterprise data initiatives.
Oversee development and maintenance of management reporting related to key business and operational metrics.
Design and automate recurring reports, scorecards, and dashboards.
Analyze trends in loss frequency, severity, geographic performance, customer behavior, operational effectiveness, and product performance.
Present analytical findings and business recommendations to leadership and stakeholder groups.
Lead cross-functional analytical projects from concept through implementation.
Manage project plans, priorities, deliverables, and stakeholder communications.
Drive analytical initiatives that support strategic business objectives and product enhancements.
Coordinate with technology teams on system enhancements, data requirements, and testing activities.
Support production implementation of analytical models and business solutions.
Automate and optimize processes to improve efficiency, scalability, and data quality.
Research and evaluate emerging technologies, analytical techniques, and best practices.
Identify opportunities to increase business value through advanced analytics and process innovation.
Consult with business partners on analytical strategies, decision support, and performance improvement initiatives.
Provide guidance and technical leadership to junior analysts and team members.
Review analytical work products and coach others to ensure quality and consistency.
Develop and deliver training on analytical methods, tools, data interpretation, and business applications.
Foster a culture of continuous learning and analytical excellence.