Data Analyst I Product

Accountabilities: Gather, organize, and prepare internal and external data for analysis, checking completeness and accuracy and flagging potential data-quality issues. Analyze product performance and competitive data to identify trends, differences, risks, and opportunities. Support recurring and ad hoc analyses focused on product performance and competitive positioning. Create and maintain reports, charts, spreadsheets, and basic dashboards to communicate findings. Assist with data ingestion, cleanup, and documentation for competitive intelligence used in personal lines analysis. Use established SQL queries, analytical code, and reporting processes, making routine updates and requesting review for significant changes. Document analytical methods, assumptions, and results to ensure work is clear, consistent, and reproducible. Collaborate with Product and cross-functional partners to understand data requirements and provide analytical support. Contribute to small-scale projects and process improvements, escalating questions, unexpected findings, and data-quality concerns when appropriate. Share analytical findings with colleagues and managers, helping develop recommendations under the guidance of senior team members. Perform other related duties as assigned. Requirements: A bachelor's degree in mathematics, statistics, economics, data science, engineering, finance, or another analytical discipline is preferred. An equivalent combination of education and experience may also be considered. At least one year of experience in data analysis, product development, competitive intelligence, insurance, financial services, or a related field is preferred. Experience in property and casualty insurance or personal lines is an advantage. Proficiency in SQL and Microsoft Excel, with experience using these tools to organize, validate, and analyze data. Foundational analytical and statistical skills, including the ability to interpret results and recognize when further review is needed. Exposure to Python, R, dbt, Git/GitHub, or business intelligence and reporting tools is a plus. Ability to work with structured datasets, follow established procedures, and perform basic data-quality checks. Strong attention to detail, problem-solving abilities, and eagerness to learn new tools and business processes. Clear written and verbal communication skills, with the ability to explain analytical findings in a straightforward way. Ability to collaborate with cross-functional teams and manage assigned tasks effectively with appropriate guidance. Benefits: Competitive annual base salary, with location-based ranges: California: $81,341–$112,974. New Jersey, New York, Washington, Hawaii, Alaska, Maryland, Connecticut, Rhode Island, and Massachusetts: $63,410–$117,348. Nevada, Oregon, Arizona, Colorado, Wyoming, Texas, North Dakota, Minnesota, Missouri, Illinois, Wisconsin, Florida, Georgia, Michigan, Ohio, Virginia, Pennsylvania, Delaware, Vermont, New Hampshire, and Maine: $57,646–$106,680. Utah, Idaho, Montana, New Mexico, South Dakota, Nebraska, Kansas, Oklahoma, Iowa, Arkansas, Louisiana, Mississippi, Alabama, Tennessee, Kentucky, Indiana, South Carolina, North Carolina, and West Virginia: $51,881–$96,012. Compensation may vary based on location, relevant experience, and skills. Remote work flexibility from anywhere in the United States for most positions. Paid time off, including vacation and sick leave, nine paid company holidays, and volunteer hours. Incentive bonus opportunities, including potential holiday, referral, and performance-based bonuses. Medical, dental, vision, life, and pet insurance. 401(k) retirement savings plan with company matching. Education assistance and professional and personal development opportunities. Promotional and career growth opportunities. Employee recognition programs. Health and wellbeing resources, including complimentary mental health therapy and coaching sessions, as well as childcare and eldercare support. A collaborative and engaging work environment.