Top Data Analyst Jobs in Chicago, IL

The Data Analyst position requires U.S. citizenship and that all work be performed within the continental United States, Alaska, or Hawaii. The listed annual pay range is $90,000 to $110,000.

Analyzes, validates, and maintains provider data for credentialing, enrollment, health plan rosters, and regulatory submissions. The role performs data reconciliation, quality checks, reporting, exception resolution, and audit support while collaborating with credentialing, operations, compliance, contracting, enrollment, and IT teams. It also supports process improvement, automation, data governance, system testing, and documentation to improve provider data accuracy and submission timeliness.

Leads complex, cross-functional business intelligence initiatives from strategy and scoping through delivery. Partners with senior leaders across Sales, Marketing, Finance, and Operations to build scalable data products and actionable insights. Establishes standards for metrics, data modeling, governance, quality, and storytelling; designs data infrastructure using modern tools such as dbt. Drives data literacy, mentors analysts, contributes to analytics roadmaps, and ensures data assets are trusted, discoverable, secure, and fit for executive decision-making.

Lead cross-functional analytics initiatives across product, marketing, audio development, and business operations. Build data models, dashboards, self-serve reporting tools, and actionable company-wide metrics. Analyze activation funnels, A/B tests, growth KPIs, and product health while optimizing the analytics infrastructure. Partner with executives, engineering, product, marketing, and data engineering teams to improve governance, data adoption, and decision-making.

Analyze sales, marketing, and customer success performance, including pipeline, funnel conversion, campaigns, retention, and revenue drivers. Build and maintain dbt models and marts using Salesforce and modern data-stack tools, while owning data quality and documentation. Contribute to Lighthouse, a BI-as-code platform, and develop AI-assisted analytics workflows. Partner with stakeholders to frame ambiguous questions, deliver recommendations, and communicate progress in two-week sprints.

Support analytics by cleaning, validating, and transforming data; build dashboards and KPI reports; perform trend, cohort, and A/B testing analyses; improve data pipelines and forecasting; present insights to cross-functional teams.

Leads advanced data analysis to guide product and business decisions, develops metrics, dashboards, data products, and AI-enabled reporting systems, and translates findings into strategic recommendations. Partners with data engineers on dimensional data models, data governance, and quality controls. Mentors analysts, aligns roadmaps with business priorities, improves problem framing, and communicates insights effectively to technical and business stakeholders.

Support product managers and tech leads by defining backtesting and validation plans, performing data analysis and validation for client deployments, improving data flows and operations, and conducting financial securities research and modeling (regression, simulations, portfolio risk analytics).

Collects, validates, analyzes, and transforms perioperative, financial, and statistical data for recurring and ad hoc reports. Develops and maintains databases, spreadsheets, dashboards, and block-utilization analyses; identifies trends and recommends operational improvements. Collaborates with administration, physicians, Information Services, and Analytics teams, presents findings, supports reporting methodologies, and manages assigned surgery system updates.

The Data Analyst gathers and documents data requirements, queries and analyzes data, validates reporting outputs, and supports KPI tracking. The role researches data sources, assists with ETL and enterprise data warehouse integration, maintains data dictionaries and lineage documentation, identifies quality issues, and delivers reports and insights to stakeholders. Additional responsibilities include supporting data governance, PII controls, master data management, reporting automation, and cross-functional solution design.

Analyze workforce data and develop HR dashboards, scorecards, KPIs, visualizations, and automated reporting solutions. Identify trends across the employee lifecycle, evaluate engagement and employee programs, ensure data quality and compliance, and provide actionable recommendations to HR and business leaders. The role also supports employee listening strategies, reporting process improvement, data governance, and executive-level presentations.

Provides data analytics and business intelligence support for government customers. Responsibilities include gathering requirements, analyzing and transforming enterprise data, designing data models, developing dashboards and visualizations, documenting governance processes, improving workflows, and training users. The role requires government acquisition, finance, or financial management experience, preferably within DoD or Air Force systems, and supports financial office operations.

Design, implement, and validate data mapping, transformation, and integration solutions for payment integrity. Investigate and resolve complex data quality issues, create mapping specs and documentation, partner with stakeholders, and mentor analysts to improve data quality and automation.

Own end-to-end analytics for the Pro product: build production data pipelines and dbt models, define north-star metrics, design dashboards and full-funnel reporting, lead A/B experimentation and causal inference, embed AI tooling, and deliver clear data-driven recommendations to product and leadership.

Manage daily Data team operations, research and analyze datasets, build internal and external reports (including an annual Startup Ecosystem Ranking), and maintain/improve Python scripts and data infrastructure to deliver actionable insights.

Audit and reconcile marketing and lead data end-to-end, maintain campaign tracking and platform integrations, troubleshoot data flow issues, manipulate large datasets to identify discrepancies, coordinate with vendors and stakeholders, and recommend process improvements to ensure accurate marketing-to-intake reporting.

Support Head Start program data activities by collecting, cleaning, validating, analyzing quantitative and qualitative data. Produce reports, dashboards, and visualizations; monitor data quality; support program monitoring, compliance reporting, and process improvements; collaborate with stakeholders to deliver actionable insights and maintain documentation.

Support audit team by executing data-driven testing, documenting results, evaluating data quality and internal controls, and recommending improvements. Build analytical skills, communicate testing strategies, and collaborate with stakeholders while gaining foundational audit experience.

Lead analytics projects and forecasting using Power BI, SQL, Python and DAX. Develop data models, resolve data quality issues, produce dashboards and management reporting, mentor junior analysts, collaborate with finance and stakeholders to deliver actionable insights, and drive continuous improvement and automation to support strategic decision-making.

The Data Analyst will analyze data using Google BigQuery and Generative AI, optimize queries, create visualizations, and ensure data quality for strategic decisions.

The Data Analyst will support data manipulation, ingest large volumes of data, create visualizations, and conduct analyses for U.S. Customs and Border Protection.

The Data Analyst will conduct data mining, analyses, and reporting, support client applications, and work within a data science project team.

As a Data Analyst Intern, you will collect, analyze, and interpret data, create visualizations, and support reporting efforts to drive business decisions.

Lead data strategy for Stripe's risk product, design metrics and frameworks, manage data reliability, mentor analysts, and evaluate risk experimentations.

Lead data analysis efforts by building and maintaining dashboards, performing SQL queries and data quality checks, analyzing program data to inform recommendations, gathering user requirements, managing projects and UAT, training users, and providing technical support for reporting tools.