Top Data Analyst Jobs

Lead and mentor a team of analysts to deliver HR-related analytics and BI solutions. Mine and model large datasets, design tests, improve reporting and operational efficiencies, and collaborate across business units to inform strategy and product decisions.

Develops business intelligence solutions through quantitative analysis, financial modeling, data governance, and dashboard development. Partners with global stakeholders to define KPIs, manage project milestones, and deliver actionable insights to executive leadership. Builds and maintains Tableau dashboards, complex SQL queries, automated ETL workflows, and reporting solutions. Uses Python, Alteryx, and SQL to improve reporting efficiency and incorporates AI and machine learning outputs for forecasting and anomaly detection.

Leads FEMA enterprise data readiness, quality, architecture, interoperability, governance, and stewardship assessments. Defines analytics and AI automation use cases for disaster response, fraud prevention, resource planning, and operational efficiency. Develops responsible AI oversight recommendations covering privacy, fairness, transparency, human review, risk controls, and model monitoring. Translates complex data landscapes and mission needs into measurable strategic investments and actionable recommendations for data platforms, governance frameworks, and AI capabilities.

Drive growth and product decisions through experimentation, statistical analysis, metrics management, data pipelines, modeling, and dashboard development. Partner with business and product teams to answer analytical questions, build ingestion and transformation workflows with dbt, and create visualizations that enable stakeholders to explore data and act on insights.

Analyze fundraising data by building reports, dashboards, data pulls, forecasts, and operational metrics. Clean and validate Salesforce and related data, identify quality issues, document standards, and support finance reconciliation. Build lightweight tools and workflows using spreadsheets and Airtable, ensuring important data flows into Salesforce. Partner cross-functionally on reporting architecture and coach fundraisers on effective system use.

Develop scalable data processing and analytics tools for engineering and business data. Translate stakeholder problems into analytical requirements, build end-to-end ETL and relational data solutions, create user interfaces, perform exploratory analysis, detect trends and anomalies, and communicate actionable insights through effective visualizations and reporting. Collaborate with technical and programmatic teams while following production coding, version-control, and development lifecycle practices.

Analyze large-scale electronic health record and real-world data using SQL, R, and Python. Scope requests, produce research studies and results, write Databricks SQL regex queries, support customers, investigate data sources, collaborate on peer-reviewed publications, and create enablement materials for researchers.

Develops AI, analytics, SQL, Python, and Tableau solutions for Internal Audit across risk assessment, planning, testing, reporting, and continuous monitoring. Builds data extraction and reconciliation workflows, audit dashboards, repeatable testing scripts, and AI-assisted tooling. Assesses data lineage, controls, and risks across business systems, supports GRC administration, identifies automation opportunities, and trains audit staff on analytics and AI-enabled workflows.

Analyze complex construction and design project data, develop datasets, pipelines, reports, dashboards, and predictive or prescriptive models. Partner with business, IT, and data governance teams to address reporting needs, improve processes, establish metrics, manage data access, support governance, and generate actionable insights for capital portfolio decisions.

Leads data discovery, profiling, quality assessment, and Source-to-Target Mapping for wealth management data platforms. Analyzes complex financial datasets using advanced SQL, documents business rules and transformations, translates requirements for ETL and data engineering teams, supports data governance and testing, and communicates findings to technical and business stakeholders.

Leads data discovery, profiling, quality assessment, and Source-to-Target Mapping for enterprise wealth management platforms. Analyzes client, portfolio, transaction, holdings, performance, and billing data using advanced SQL; documents business rules and transformations; partners with ETL and data pipeline engineers; supports data governance, validation, testing, and stakeholder communication.

Manages healthcare data exchange operations, including EDI mapping, file transformation, validation, monitoring, troubleshooting, error resolution, partner onboarding, reporting, and process automation. The role supports medical, dental, and vision claims data while ensuring HIPAA compliance, data accuracy, and secure transfers. It collaborates with internal teams, clearinghouses, employers, providers, and third-party administrators to resolve issues and improve data integration processes.

Lead a team delivering enterprise-wide model risk reporting and AI-driven automation. Build and deploy scalable ML/AI solutions, conversational reporting, multi-agent workflows, and centralized data integrations. Drive analytics strategy, validate models and data, improve reporting and operational efficiency, and collaborate across business units.

Analyze and visualize digital channel performance, build dashboards in Power BI, consolidate multi-vendor data, apply AI agents and tools to automate reporting, derive insights to optimize marketing spend across DSP, loyalty, and CRM channels, and forecast performance to inform strategy.

Analyzes workforce data to guide hiring, retention, organizational design, and people-program decisions. Builds dashboards, reports, data models, pipelines, and governance practices; ensures HR data integrity; automates reporting; identifies workforce trends and risks; and partners with People, Finance, HRIS, engineering, and business leaders to deliver actionable insights.

Build and maintain data pipelines using ETL/ELT, Databricks, Python, Spark, and Airflow. Manage data transformations, databases, schemas, and data quality controls. Support reporting, analytics, and machine learning integrations while deploying solutions in AWS. Automate workflows, troubleshoot data issues, document processes, and collaborate with data scientists, analysts, database administrators, and business stakeholders.

Interns will code software to automate processes, scrape and collect large datasets, and conduct advanced econometric analyses to investigate fraud across finance, healthcare, and cryptocurrency domains. The role involves individual and team projects, applying data science and econometric techniques, and translating academic knowledge into real-world consulting and forensic analytics applications.

Analyzes fraud across finance, healthcare, and cryptocurrency domains using data science and econometric techniques. Responsibilities include coding process automation software, scraping and collecting large datasets, and conducting advanced econometric analysis. The intern collaborates on individual and team projects while applying quantitative academic skills to real-world investigations.

Performs rapid ad hoc and diagnostic analyses to support data-driven decisions for the Individual Investors business. Responsibilities include prioritizing requests, querying and analyzing data with SQL, Python, Excel, and statistics, developing KPIs and dashboards, identifying trends and root causes, communicating actionable recommendations, prototyping solutions, and partnering with Analytics Engineering on scalable needs.

Analyzes complex business processes, data requirements, and information systems supporting the Defense Logistics Agency. Applies DoD Business Enterprise Architecture, data modeling, enterprise architecture, systems integration, and process analysis expertise to improve data quality, interoperability, modernization, and enterprise decision-making. This fully remote role requires Secret clearance and supports AMPS program initiatives.

Own daily data operations, including data collection, pipeline monitoring, quality validation, root-cause investigation, SQL-based cleaning, and Metabase dashboards. Partner with engineering and deployment teams to resolve data issues, standardize metrics, document processes, and build tooling that improves reliability and scalability for government clients.

Manages engineering and program documentation, data records, revisions, lifecycles, change orders, and authorization workflows. Coordinates documentation releases and maintains engineering systems of record while supporting schedule adherence and detailed process compliance. Requires strong Excel, communication, analytical, and organizational skills. Preferred experience includes SAP, product data management systems, requirements activities, Jira, Confluence, and LaTeX. This is a full-time, on-site role in Rolling Meadows, Illinois, requiring the ability to obtain and maintain a Secret clearance.

Analyze customer, retailer, marketplace, sales, and syndicated market data to identify growth opportunities and inform sales and category leadership. Develop automated reports, dashboards, scorecards, and performance tracking for sales, market share, launches, and DSMP execution. Translate complex data into insights and narratives for customer presentations, category reviews, and joint business planning while ensuring reporting accuracy and cross-functional alignment.

Translate business needs into clear data requirements, design and maintain curated integrated datasets, validate mappings and lineage, support data governance and quality, enable data products for reporting and analytics, and lead small data integration and process-improvement initiatives across business, analytics, and engineering teams.

Support commercial performance, revenue management, customer analytics, sales operations, product strategy, and executive decisions. Build financial models, SQL data pipelines, quality controls, BI dashboards, automated workflows, customer health metrics, and product portfolio analyses. Partner cross-functionally with Product, Sales, Finance, Customer Care, Consulting, and leadership teams to deliver actionable insights and improve revenue retention, pricing, and product performance.