Senior Data Analyst

FCIC•Bedford Park, IL

About The Position

First Chicago is hiring a Senior Data Analyst as the dedicated data resource for its Strategic Finance unit. The role builds and maintains data extracts, analytical datasets, and reproducible reports using the enterprise data lake and source systems, so the unit can work with timely, reconciled, and documented data. The position reports to the Chief Accounting Officer & Treasurer. Its first priority is supporting the Senior Strategy & Performance Analyst’s investigations, action tracking, and executive reporting, beginning with Claims data. Financial Planning & Analysis and special projects are supported as capacity permits. The analyst supplies data and reporting to the unit but does not own enterprise KPI definitions, source systems, or conclusions drawn from analysis. The role covers claims, policy, premium, and financial data at the levels investigations require, including carrier, state, program, product, distribution channel, department, and vendor. It also maintains a data dictionary and lineage documentation, applies enterprise KPI definitions where available, and documents supplemental definitions where needed. Primary areas of focus are strategy and performance analysis, with Claims data first. This includes severity and frequency, loss and loss adjustment expense, loss development, cycle times, attorney representation, litigation, complaints, vendor costs, and state or program variances. The analyst may also support budgeting, forecasting, modeling, variance analysis, and special projects as capacity permits. Actuarial analyses and judgments remain with Actuarial, while source systems and data corrections remain with their owners. Success is measured by timely delivery of data for investigations; datasets reconciled to control totals at release; documented, reproducible queries and reports that refresh without rework; reduced manual effort through automation; data-quality issues identified, escalated, and tracked to resolution; and users’ confidence in the numbers provided. Success is not measured by the volume of reports or dashboards produced.

Requirements

Bachelor’s degree in Data Analytics, Statistics, Computer Science, Information Systems, Finance, Accounting, Economics, or a related field, or equivalent experience.
Five or more years of data analysis, business intelligence, or reporting experience, including work in insurance or financial services.
Advanced SQL skills, including complex joins, window functions, and query performance on large datasets.
Experience in a data lake or cloud data warehouse environment.
Proficiency with BI/data visualization tools and advanced Excel.
Working knowledge of P&C insurance data, including policy and premium, claims, loss and loss adjustment expense transactions, accident-year and calendar-year views, and financial reporting concepts.
Disciplined approach to validation, reconciliation, documentation, and version control.
Ability to explain data limitations clearly to non-technical audiences.
Discretion with confidential information.

Nice To Haves

P&C insurance data experience.
Scripting experience, such as Python, for data preparation and automation.

Responsibilities

Build and maintain data extracts and analytical datasets from the enterprise data lake and source systems, covering claims, policy, premium, and financial data at the detail level required for investigations.
Develop documented, reproducible queries and reports that can be refreshed, reviewed, and rerun without manual rework.
Reconcile datasets to the general ledger, financial reporting, and system control totals before release; document reconciling differences and their causes.
Identify and document data-quality issues, escalate source-system defects to responsible data owners, and track them to resolution.
Maintain a data dictionary and lineage documentation for the unit’s datasets, applying enterprise KPI definitions where they exist and documenting supplemental definitions.
Supply data for action tracking and monthly executive summaries, including documented baselines and post-implementation measurement of improvement initiatives.
Use existing enterprise reports when timely and sufficient, and build supplemental data and reports only when needed.
Automate recurring extracts and reports where automation reduces manual effort and error risk.
As capacity permits, support Financial Planning & Analysis with data for budgeting, forecasting, modeling, and variance analysis.
Provide data and analysis support for special projects as assigned.