Senior Principal Data Analyst

Role overview Lead complex analytics work that turns business questions into dependable data solutions, reporting, and recommendations. The role combines analysis and modeling with data quality and governance, project leadership, and communication with business and technical partners. Work may support functions such as claims, underwriting, marketing, advertising, and product management, and includes coaching other analysts.

Responsibilities - Design and maintain data models, analytical solutions, reports, and dashboards; manage extraction, transformation, and validation to support accurate results. - Translate business problems into analytical approaches and actionable recommendations, using statistical analysis, data mining, forecasting, and research. - Oversee data sources and governance practices; check data for completeness and reasonableness, and document definitions, rules, specifications, and methods. - Lead cross-functional analytics projects from exploration and planning through implementation, coordinating deliverables, stakeholders, technology needs, and testing. - Improve reporting and analytical processes through automation; evaluate new data sources, tools, and methods, and identify opportunities to improve business performance. - Review colleagues’ work, provide technical guidance, and share knowledge through coaching and training.

Requirements - Bachelor’s degree in a quantitative field such as statistics, mathematics, data science, economics, computer science, engineering, or operations research; a master’s degree or doctorate is preferred. - At least 9 years of analytical experience with a bachelor’s degree, or 7 years with a master’s degree. - Experience leading complex analytical projects and cross-functional initiatives, with the ability to explain findings to technical and non-technical audiences. - Advanced SQL or SAS SQL skills, strong R proficiency, experience with cloud data platforms, and advanced Excel skills. - Experience creating analytical reports, dashboards, and data models, and applying statistical, mathematical, and data-mining methods to business problems. - Ability to manage competing priorities, work independently and collaboratively, and learn complex technical and business concepts.

Nice to have A quantitative doctorate or master’s degree, Python, BI tools such as Power BI or Tableau, machine learning or predictive modeling, and experience in insurance, financial services, or data-intensive business areas such as claims, underwriting, marketing, product management, or pricing.

Benefits and work setup The source describes development programs, mentorship, certification assistance, competitive compensation, benefits, and flexibility. Sponsorship may be considered for a qualified applicant.