Top Data Analyst Jobs

Analyze and maintain manufacturing data systems, develop KPI dashboards, ensure reporting accuracy, and provide data-driven insights for engineering projects and cause investigations. Collaborate with operations, process engineering, quality, and manufacturing associates, occasionally collecting data on the shop floor and supporting compliance with quality standards.

Analyzes and interprets data for community health research projects, including NIMH-funded implementation and intervention development studies. Responsibilities include data preparation, statistical analysis, predictive modeling, data mining, reporting, dashboard development, quality checks, trend identification, and presenting findings. The role collaborates across teams, manages multiple projects, recommends actionable insights, and may guide less experienced analysts.

Conducts data collection, cleaning, management, statistical and computational analysis for education policy research. Responsibilities include building reproducible ETL pipelines, creating visualizations and research materials, applying machine learning and natural language processing, validating model outputs, managing restricted-use data, reviewing analyses, and coordinating with external collaborators. Senior responsibilities include overseeing analytical projects, documenting methodologies, managing compute and API costs, and serving as a technical contact.

Maintains accurate records across spreadsheets, databases, and internal systems. Reviews and verifies information, identifies discrepancies, organizes digital files, updates records, prepares simple reports, and supports basic research. The role requires strong attention to detail, confidentiality, reliable independent work, and proficiency with spreadsheet and document-management tools in a remote environment.

Design and maintain billing data systems that reconcile patient engagement data, codify auditable billing logic in BigQuery SQL, automate data cleanup with Python or Google Sheets scripting, and generate accurate, version-controlled invoice files. Investigate mismatches and edge cases, document workflows, and collaborate with Finance, Sales, Engineering, and Product to improve billing inputs and processes.

Develop data solutions, business intelligence tools, dashboards, and analytical insights while managing data quality, metadata, lineage, security, access governance, and data quality monitoring. Partner with business and technology teams to address complex data problems and enable self-service analytics. The role requires scripting, querying, visualization, AWS development, and data governance expertise.

Analyzes digital product usage, customer behavior, performance, and business data to drive product adoption and outcomes. Develops KPIs, dashboards, reports, measurement frameworks, and business insights; validates data quality and supports governance. Partners with Product, Finance, Technology, and business stakeholders on prioritization, ROI analysis, product roadmaps, and continuous reporting improvements. Translates complex findings into actionable recommendations and supports self-service reporting solutions.

Manage a team of 2–3 analysts while remaining hands-on with SQL, dbt models, dashboards, and complex operational analyses. Lead ambiguous, cross-functional initiatives, deliver recommendations to senior stakeholders, ensure data quality, and improve reporting automation. Partner on AI analytics strategy, data readiness, agent evaluation, and human-in-the-loop governance. Responsibilities include coaching, prioritization, performance management, technical review, KPI development, and operational insights across customer experience, fraud, payments, workforce management, and VIP functions.

Conducts exploratory and defined analyses of criminal justice datasets, identifies trends and discrepancies, prepares analytical data for state product launches, and builds documented visualizations and dashboards. The analyst communicates findings to internal teams and state partners while collaborating with senior analysts and engagement teams. Responsibilities include cleaning real-world data, supporting product launches, evaluating product impact, and developing expertise in assigned states’ data, policies, and products.

Develops maintenance training metrics covering schedule execution, student feedback, training impact, and return on investment. Analyzes survey responses, identifies trends, and recommends schedule, curriculum, and process improvements. Prepares summary reports and presentations for program reviews and staff knowledge support. Requires five years of data analysis experience supporting complex projects, database design experience, Microsoft Office proficiency, U.S. citizenship, and eligibility for a Secret clearance.

Provides first-line BI support for tickets, emails, and incidents across business divisions. Designs, builds, and supports Power BI reports; triages stakeholder issues; manages SLAs; performs minor enhancements and bug fixes; communicates support performance; collaborates with IT teams; and identifies automation and process-improvement opportunities.

Analyze manufacturing and engineering data to identify trends, risks, inefficiencies, and cost-saving opportunities. Build datasets, dashboards, and reports using SQL, Python, Excel, and Power BI or Tableau. Support CAPEX financial analysis, ROI and payback modeling, operational KPI tracking, data validation, continuous improvement, and process optimization. Collaborate with engineering, operations, maintenance, finance, and leadership teams in an onsite manufacturing environment.

Analyze Experian portfolio repayment performance, credit risk, underwriting and credit-limit changes, collections, funnel metrics, cohort LTV, and unit economics. Own partner analytics models, data definitions, reporting, alerting, and data quality monitoring. Collaborate with Product, Engineering, Partnerships, Finance, and Experian to guide roadmaps, evaluate experiments, identify risks, and support business reviews.

Designs and maintains Power BI reports and dashboards using Microsoft Fabric semantic models. Builds data models, writes and optimizes DAX, applies security controls, validates data quality, and creates certified datasets and reusable templates. Partners with stakeholders to define reporting requirements, presents insights, participates in peer reviews, and uses AI tools to improve analysis and delivery.

Designs and maintains Power BI reports and dashboards using Microsoft Fabric semantic models. Responsibilities include data modeling, DAX development and optimization, report validation, security governance, stakeholder requirements gathering, self-service dataset creation, and presenting insights. The role also requires collaboration across teams and use of AI tools to improve analysis and delivery.

Build and maintain Power BI reports and dashboards using Microsoft Fabric semantic models. Translate business requirements into data models, visualizations, and DAX measures; apply security and governance standards; validate data quality; create certified datasets and reusable templates; and collaborate with stakeholders to turn reporting insights into business decisions. The role also requires using AI tools and supporting peer reviews and self-service analytics.

Build and maintain Power BI reports and dashboards using Microsoft Fabric semantic models. Responsibilities include data modeling, DAX development and optimization, report validation, security implementation, stakeholder requirement gathering, certified dataset creation, and cross-team presentation of insights. The role also requires using AI tools, supporting self-service analytics, and collaborating on peer reviews and data-quality initiatives.

Analyze and visualize large customer datasets, build production-grade data models and scalable data products, automate manual analytical workflows, and create AI-assisted, conversational, and self-service analytics experiences. Translate ambiguous stakeholder needs into actionable solutions while collaborating across teams and experimenting with generative AI and modern data technologies.

Analyze live game performance, player behavior, retention, engagement, and monetization. Build dashboards, write SQL queries, conduct A/B tests, establish telemetry and analytics practices, and communicate actionable recommendations to LiveOps, design, publishing, and executive stakeholders. Support data-driven optimization of game features, events, promotions, and in-game economies across development and post-launch stages.

Owns the marketing data and analytics ecosystem, building SQL-backed datasets, Tableau dashboards, KPI reporting, attribution analysis, and experiment measurement. The role monitors data quality, troubleshoots tracking across marketing platforms, analyzes channel and funnel performance, and delivers actionable insights to Marketing, Sales, agencies, and leadership. It also supports budget allocation, lead quality, conversion analysis, and marketing testing.

Analyze client performance, KPIs, utilization trends, and operational benchmarks using large healthcare datasets. Build reporting views, dashboards, reusable queries, models, and notebooks for Client Success and Operations. Conduct cohort, benchmarking, root-cause, and network opportunity analyses, then translate findings into clear narratives for executives and clients. Partner with analytics leadership to improve analytical standards, documentation, and reusable frameworks.

Analyzes datasets to identify trends and insights supporting organizational decisions. Develops and manages data sources for demand and capacity planning, source and supply planning, process efficiency, and quality management. Uses Microsoft tools and visualization platforms such as Power BI, Qlik Sense, or Tableau. Requires strong analytical, organizational, communication, and time-management skills, with the ability to manage multiple priorities and work independently.

Owns automated dashboards, SQL-based analysis, data pipeline monitoring, exploratory analysis, and executive recommendations. The role tracks marketplace KPIs such as customer lifetime value, acquisition costs, churn, and provider utilization while partnering with engineering and product teams on data requirements. It is fully remote within the United States and requires advanced SQL, dashboard development, and strong analytical communication.

Analyze complex quantitative and qualitative datasets for federal consulting engagements. Develop forecasts, scenario models, dashboards, visualizations, survey analyses, executive presentations, and data-driven recommendations supporting workforce planning, organizational assessments, program evaluations, and operational improvement. Collaborate with clients and multidisciplinary teams, facilitate working sessions, and contribute to proposals and internal capability development.

Own marketing analytics across attribution, channel efficiency, experimentation, incrementality, unit economics, GTM analytics, lifecycle marketing, and reporting. Define marketing data models, build dbt models and Looker reporting, evaluate campaign and channel performance, and guide budget allocation. Partner with marketing leaders and executives to turn data into actionable decisions, improve measurement, and establish a trusted, data-driven marketing engine.