Business Intelligence Manager, Westchester

JOB SUMMARY:

Technical expert that will build and manage agile data architecture to serve analysis needs of Westchester Business Analytics team. This role will be responsible for all aspects of data management from defining data models to integrating data into reports, visualizations, and dashboards. This includes managing existing data and reporting processes that harness, manipulate, and integrate data into analytics. This role will also work on building the next level of advanced analytical processes and automations, enabling more accurate and faster information delivery to support critical business decision-making.

Critical factors for success include delivering results while maintaining a detailed focus, ability to take ownership and meet deadlines, and being a self-motivated team player coupled with the ability to work independently. Successful candidates will be adept at identifying issues and developing sound recommendations for remediation, demonstrate a willingness and desire to continuously build on insurance and product knowledge, and thrive in a fast-paced environment.

RESPONSIBILITIES:

• Support data management function of Westchester Business Analytics team related to recurring and ad-hoc reporting and analysis. This includes utilization of all available data from various systems via extraction, transformation and loading into analytical applications.
• Using data mining steps, proactively prepare data models that address common business questions and measure impact of business initiatives.
• Assemble data from multiple sources including underwriting, claims, actuarial, and product databases to create integrated views that can be easily consumed to drive decision-making.
• Query and manipulate data in relational databases using advanced tools and techniques (e.g., SQL, Netezza, SAS, Python).
• Design and build automated data connections and reports in various data visualization tools (e.g., QlikView and Qlik Sense, Tableau, Power BI) using input from business leaders.
• Identify opportunities to improve data quality, validation, automation, efficiency, and overall process improvement.
• Explore new data models, software, and algorithms that continue to improve data visualization, presentation, and ease of information delivery to our business partners.