Top Data Analyst Jobs

Own support analytics for User Operations: build dashboards and recurring reports, track north-star metrics (cSAT, TTR, QA, escalations), instrument Zendesk, connect support to product/customer data, quantify operational costs of bugs, and measure AI-driven support performance.

Own support analytics for User Operations: build recurring reports and self-serve dashboards, track north-star metrics (cSAT, TTR, QA, escalations), instrument Zendesk, connect support data to product/customer sources, quantify operational cost of bugs, measure AI-driven support impact, and deliver ad hoc analyses to inform Product, Engineering, and leadership.

The Data Analyst role involves utilizing SQL and Python for data integration, analyzing national security issues, and presenting insights to clients, requiring travel to client sites.

Provide 24/7 completions data support: enter and QAQC frac and wireline data, build and maintain dashboards, communicate with customers, test staging systems, produce daily reports, identify anomalies, and improve operational procedures.

Support hypersonic vehicle test programs by collecting, cleaning, analyzing, and visualizing test data; develop test plans and analysis methodologies; participate in design and readiness reviews; coordinate with engineering teams and customers; and support test execution and post-test data reviews.

The Business Analytics Associate analyzes marketing channel performance and client retention, presenting actionable insights to enhance company goals and KPIs.

Own analytics for the clinician lifecycle, from recruiting and credentialing through performance, quality, retention, and business impact. Build operational scorecards, predictive retention models, licensing dashboards, and transcript-based empathy scoring frameworks using SQL, Python, BI tools, NLP, and LLMs. Partner with clinical, quality, operations, talent, product, and executive stakeholders to connect clinician behaviors and outcomes with patient retention, NPS, compensation, training, and workflows.

Eight-week client-facing analytics internship involving large datasets, customized analyses, advanced statistical models, and model development or validation. The analyst will collaborate with consulting teams and clients, summarize and document findings, and present client-ready solutions. Candidates should have quantitative academic backgrounds, experience with R, SQL, and Python, strong communication and teamwork skills, and unrestricted U.S. work authorization.

Partner with cross-functional teams to design experiments, analyze large datasets, build dashboards and metrics, identify trends and customer behaviors, improve data quality and instrumentation, and provide actionable recommendations that drive strategic decisions and operational improvements.

Transform clinical, operational, and financial data from EHR, PM, and oncology systems into dashboards and reports. Build and maintain ETL pipelines and standardized datasets, analyze revenue cycle, clinical quality, and service-line performance, and deliver actionable insights to physicians, executives, and operational teams to improve efficiency, financial outcomes, and patient care.

Perform performance analytics, reporting, and customer segmentation for sportsbook generosity campaigns. Analyze customer behavior and promotional engagement, build hypotheses, validate data quality, maintain reporting, create clear visualizations, and collaborate with stakeholders to optimize campaign performance. Use SQL and Excel daily and leverage AI responsibly to accelerate analysis.

Build and maintain revenue and customer-lifecycle reporting, author complex BigQuery SQL, develop segmentation and clustering models in BigQuery ML, perform entity resolution and data quality reconciliation, migrate and maintain Tableau dashboards, and deliver ad-hoc and recurring analyses to support Sales, Revenue, and cross-functional teams.

Analyze and design enterprise healthcare data solutions using Snowflake and advanced SQL. Perform data profiling, reconciliation, anomaly detection, source-to-target validation, and quality testing across claims, membership, provider, and health plan data. Support data architecture, dimensional modeling, governance, metadata, lineage, cataloging, and MDM initiatives. Prepare data for AI and advanced analytics, translate business requirements into solutions, resolve data issues with stakeholders, and communicate actionable insights while following security and HIPAA requirements.

The Data Governance Analyst implements and manages enterprise data governance initiatives, including data quality, metadata, data cataloging, master data management, and profiling. The role partners with data owners, stewards, and technical teams to establish standards, maintain business definitions and lineage, monitor quality metrics, resolve data issues, support MDM processes, improve data capture, and promote governance adoption and data literacy.

Develops business cases, financial and operational models, data models, executive decision packages, portfolio dashboards, and benefit-validation reporting for cross-functional transformation initiatives. Extracts and analyzes enterprise data using SQL, Python, spreadsheets, and visualization platforms; automates repeatable workflows; standardizes metrics; tracks value realization; and partners with Finance, IT, data engineering, and business leaders to support decisions and embed sustainable reporting processes.

Partner with Marketing, Sales, Finance, Product and other teams to turn business questions into actionable analysis. Own end-to-end analytics: build datasets and dashboards (dbt, LookML), maintain metric definitions and caveats, use and curate agent tooling for trustworthy answers, and contribute small data platform and pipeline improvements.

Senior Business Analyst partnering with Finance, HR, and engineering stakeholders on data warehouse and Microsoft Fabric initiatives. Responsibilities include requirements gathering, source-to-target mapping, documentation, data quality and migration validation, Power BI monitoring, governance and security requirements, UAT leadership, defect tracking, and stakeholder sign-off. The role handles sensitive HR and Finance data and translates business needs into technical specifications and production-ready data products.

Performs complex healthcare data analyses, including MCO encounter data validation, quality assurance, and performance measurement. Develops queries, reports, and Tableau dashboards; translates business requirements into analytical solutions; and communicates results to clients and stakeholders. Identifies automation and workflow improvements while ensuring data accuracy, regulatory compliance, and timely deliverables. Supports HEDIS and CMS-related analytics and manages multiple projects in an office-based environment.

Leads advanced data analytics, statistical modeling, predictive analytics, and business intelligence for supply chain and logistics operations. Analyzes complex datasets, develops forecasting and optimization models, creates Tableau or Power BI dashboards, monitors KPIs, and translates findings into recommendations for government stakeholders. Provides technical leadership, quality oversight, and mentorship to junior analysts.

Gather and document business and data requirements, translate needs into functional specs and source-to-target mappings, write SQL to profile and validate data, interpret Duck Creek policy XML and map to Insights tables, collaborate with developers/data engineers, support data quality/governance and reporting, facilitate stakeholder meetings, and assist support teams with data issue analysis.

Analyze client platform data to identify trends, forecast needs, and support mission objectives. Define analytical requirements, ensure data quality and governance compliance, create reports, dashboards, and performance metrics, and integrate data from multiple sources. Validate and document data, collaborate with technical teams to improve systems, develop reusable analytical components, evaluate analytics tools, and train users on analytics capabilities.

The Data Analyst II is responsible for designing, developing, and administering data constructs, ensuring data quality, and working with large data sets while coordinating multiple streams of work.

Verify and maintain database master and control file metadata; identify, research, and resolve data errors; generate and respond to reports; document system files and reports; recommend improvements and coordinate modifications; learn legacy source systems and perform source-to-target data mapping to support analytic data lineage.

Provide and develop timely reports from the data warehouse using BI tools and SQL; maintain and build reports and database applications; design and validate ETL processes and data transforms; administer CRM and Accelehealth; support QA, documentation, and project reporting; ensure EPHI access compliance and provide backup to senior systems analysts/project managers.

Design, build, and maintain SSIS-based ETL templates to convert legacy customer data into corporate systems. Support ETL leads, perform QA on data conversion projects, and document/refine ETL policies and procedures to ensure accurate integrations and a strong customer experience.