Data Analyst

PMA’s Risk Control Department is seeking a self‑motivated, solution‑oriented Data Analyst who enjoys building the data models, tools, systems, and processes necessary to enhance and streamline the way data is utilized and processed currently. As a member of our Risk Control Department, you will have the opportunity to positively impact efficiency and profitability by designing, and re‑designing the way data is extracted, transformed, loaded.

You will perform assignments, tasks or activities that directly and indirectly contribute to the fulfillment of the corporation's and department's overall business objectives.

• Collect, evaluate, run, and design statistical data/reports on a monthly and ad hoc basis.
• Prepare statistical and narrative reports and recommendations and participate in the analysis and interpretation of data as appropriate.
• Support various project initiatives.
• Develop, maintain, and ensure quality control of data sources, queries, models, and results.
• Run existing analytical reports and assist with defining and designing new reports to meet business needs.
• Utilize data visualization tools to effectively illustrate data trends and patterns.
• Participate in the development, implementation, and enhancement of data models and data warehouse tables to ensure that business needs are met.
• Develop and implement data query and mining techniques that optimize statistical efficiency and data quality. This may include cleansing and normalizing of data or development of internal control reporting to ensure data validity going forward.
• Assists in the application and implementation procedures of data standards and guidelines to ensure access to and integrity of data sets.
• Identify, troubleshoot, and remediate issues that are produced from anomalies in the data.
• Develop self‑service reporting and informational tools for end users through defining business requirements, application and/or query design, testing, solutions implementation and end user training.
• Assist in the testing and implementation of new or upgraded software.
• Work closely with management and other department heads to prioritize business and information needs.
• Provide data consulting in support of business and information technology initiatives to stakeholders to improve database systems.
• Assist in the development of a system by which other analysts may be effectively educated on the various data analyst techniques employed.
• Collaborate with both internal and external stakeholders to clearly define and document information/data requirements.
• Support compliance and audit requirements.
• Demonstrate commitment to Company's Code of Business Conduct and Ethics, and apply knowledge of compliance policies and procedures, standards and laws applicable to job responsibilities in the performance of work.

• BS in Mathematics, Economics, Business, Risk Management, Computer Science, Information Management, Statistics or related fields.
• Experience as a data analyst in commercial casualty insurance industry, with emphasis in workers compensation preferred.
• Adept at query development, report writing and presenting findings.
• Understanding of data modeling and data cleansing techniques.
• Strong analytical skills with the ability to collect, organize, analyze, and communicate significant amounts of information with attention to detail and accuracy.
• Excellent visual design sense regarding clear and accurate presentation of data.
• Ability to interact with business and technology experts to help determine the technical feasibility of requirements.
• Ability to effectively communicate technical concepts to both technical and non‑technical audiences.
• Ability to organize and balance multiple concurrent timelines and tasks to meet deadlines.
• Superb business process analysis and interpersonal skills.
• Strong knowledge of tools such as Excel, Access, Power BI, Visual Basic, database development.
• Working familiarity with tools such as Qlik Sense, Tableau, Hyperion, Access, SharePoint, Micro Strategy, SQL, R and Python preferred.