Top Data Analyst Jobs

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.

Build and maintain scalable batch and real-time data pipelines for financial and alternative datasets. Productionize AI/ML workflows for document extraction, classification, and data processing; own model evaluation, monitoring, and human review. Design investment data models, validation, anomaly detection, and reconciliation systems. Partner with quants and data scientists to operationalize research signals, onboard vendors and datasets, integrate APIs, and improve data reliability using modern cloud, streaming, orchestration, and warehouse technologies.

Analyzes customer and business requirements, data, test results, and program outputs to implement accurate batch data fulfillment solutions. Serves as a liaison between business, technical, and operational teams; configures systems, executes test plans, troubleshoots processing issues, maintains documentation, and ensures compliance with legal and operational standards. The role also supports process improvements, cost reduction, quality initiatives, and timely program delivery using proprietary systems.

Develops interactive dashboards, visualizations, and recurring reports that help cyber defense commanders and analysts understand risk, readiness, and mission impact. Creates autonomous visualization products, supports leadership’s ad hoc reporting needs, applies visualization best practices, and maintains templates and standards. Requires expertise with BI tools, Python visualization libraries, SQL, and data visualization principles, along with a DoD TS clearance and SCI eligibility.

Maintain and integrate investment data; build data systems and ETL pipelines; analyze large datasets; produce visualizations and reports (Tableau/Power BI/D3.js); improve data quality and governance; develop analytical tools; collaborate with clients, system architects, and product teams.

Build scalable data pipelines, dashboards, visualizations, and automated risk and compliance workflows using Python, Spark, Airflow, SQL, and generative AI. Perform exploratory and statistical analysis to identify insights, anomalies, and operational improvements. Partner with Operations, Compliance, Product, and Engineering to deliver data-driven solutions and support strategic initiatives.

Reviews, validates, organizes, and prepares asset datasets for reporting and visualization. Identifies missing, duplicate, inconsistent, or inaccurate information; applies data standards; documents corrections and exceptions; coordinates issue resolution; and supports repeatable data-management and process-improvement procedures. The role requires Excel proficiency, strong attention to detail, clear communication, independent work, collaboration, and a Top Secret clearance.

Designs and manages workforce surveys, facilitates focus groups, cleans and analyzes qualitative and quantitative data, and develops dashboards, visualizations, and executive presentations. Partners with stakeholders to identify trends, measure organizational effectiveness, and provide actionable workforce insights. Uses relational databases, visualization tools, and large language models to support longitudinal analysis and open-ended response analysis for Intelligence Community customers.

Own marketing analytics and measurement to improve acquisition, campaign performance, and marketing ROI. Lead multi-touch attribution, marketing mix modeling, A/B testing, incrementality studies, and KPI analysis. Partner with Marketing and Product to improve data quality, translate complex findings into recommendations, influence senior stakeholders, and coach peers on analytics practices.

As a Principal Data Analyst, you will innovate and manage data solutions, provide business intelligence, and ensure data quality for the Retail Bank.

Build and manage Power BI dashboards and reports for fundraising performance, analyze large datasets and KPIs, identify trends, improve data workflows, and translate findings into clear recommendations. Partner with fundraising, marketing, analytics, and leadership teams to support data-driven decisions. The role requires advanced SQL, strong data visualization, fundraising or financial analytics experience, and a relevant bachelor’s degree.

Supports strategic pricing through competitive price reports, Power BI dashboards, Snowflake data queries and joins, pricing performance tracking, sales deal evaluation, exception pricing requests, and ad hoc projects. Collaborates with Finance, Marketing, Product Management, and Sales while developing pricing strategy and analytical skills.

Analyze marketing and media data to measure TV and streaming campaign effectiveness, validate data and assumptions, identify actionable insights, and create clear visualizations and client-ready presentations. The analyst will use Excel, BI and data platforms, SQL, and AI tools to accelerate analysis while independently validating results and explaining methodologies, KPIs, and recommendations to internal teams and clients.

Analyze and visualize data, define product and business metrics, develop reliable data models and pipelines, and build self-service dashboards and datasets. The role supports product performance, user research, business strategy, and customer satisfaction while collaborating with data scientists, analysts, engineers, and cross-functional stakeholders. Responsibilities include maintaining data models, troubleshooting analytics solutions, and contributing through discussions and code reviews.

Analyze and visualize data to solve product, business, and operational problems. Define performance metrics with stakeholders, develop and maintain accurate data models, and build datasets, dashboards, self-service tools, and data pipelines. The role uses SQL, Python, Git, dbt, and Omni, supports geospatial and enterprise data analysis, and contributes to a collaborative team through discussions and code reviews.

Two-year rotational program for graduating students to analyze structured and unstructured data, develop dashboards and visualizations, apply SQL/Python/Tableau/Power BI, partner with business teams, and deliver insights that influence strategy and improve client and operational outcomes.

Two-year rotational program for recent graduates to analyze structured and unstructured data, build dashboards and visualizations, partner with business and tech teams, apply data governance, and deliver insights using SQL, Python, Tableau and cloud platforms to influence strategy and improve client and operational outcomes.