Top Data & Analytics Jobs

Designs and owns analytics solutions for business stakeholders, including dbt data models, advanced SQL transformations, data quality controls, semantic layers, Looker and Power BI dashboards, and automated reporting. Performs exploratory and root-cause analysis across revenue, sales, retention, margin, and operations; reconciles results with finance systems; documents metrics and lineage; and supports BI platform modernization and post-merger integration. The role requires strong stakeholder communication, analytics engineering, cloud data platform expertise, and production-quality development practices.

Performs data quality assurance for large datasets by validating imports, updates, transformations, and extracts. Writes SQL test queries, reviews database logic, executes test cases, identifies defects, verifies corrections, and documents testing results. Collaborates with data engineers, business analysts, project managers, and QA professionals to ensure data integrity and compliance with requirements.

Lead supply chain analytics and AI initiatives focused on MRP accuracy, inventory optimization, production scheduling, and process improvement. Develop statistical, machine learning, generative AI, and reporting solutions; manage supply chain metrics and data governance; optimize SAP MRP parameters; support SIOP planning; and partner with procurement, manufacturing, engineering, and IT teams. Mentor analysts and data scientists while driving automation, analytics strategy, and measurable operational improvements.

Own end-to-end analytics for subscription products and web funnels, including KPI definition, dashboards, funnel and cohort analysis, payment performance, user behavior, experimentation, and anomaly monitoring. Build reliable SQL data models and maintain event taxonomies and tracking. Partner cross-functionally with Product, Marketing, Engineering, Finance, and BI to improve conversion, retention, revenue, and LTV. Mentor analysts and communicate actionable recommendations to stakeholders.

Design, build, and maintain data solutions to support enterprise risk. Partner with business to produce dashboards and analyses, drive data quality, metadata and lineage practices, manage data access governance, and use open-source tools and cloud services to enable self-service analytics.

Manages and prepares data from internal and external sources, validates data quality, performs descriptive, predictive, and prescriptive analysis, and documents methodologies and outcomes. Develops and maintains self-service reporting tools and dashboards, supports regular and ad hoc reporting, trains customers, and presents audience-appropriate findings. Identifies anomalies, investigates root causes, ensures reproducibility, and provides recommendations to support data-driven underwriting and actuarial decisions.

Manages and prepares data from internal and external sources, evaluates data quality, performs descriptive, predictive, and prescriptive analysis, and documents reproducible methodologies. Develops and enhances self-service reporting and analytics tools, gathers requirements, manages delivery milestones, trains customers, and presents findings to support data-driven decisions. Requires strong data interpretation, visualization, database, OLAP, and communication skills, with knowledge of SQL, R, SAS, or SPSS.

Analyzes marketing and CRM data, builds KPI dashboards, provides campaign and business development recommendations, and manages Salesforce administration, automation, audits, permissions, and data quality. The role validates integrations, supports migrations, troubleshoots system discrepancies, identifies enrichment opportunities, and provides user onboarding, training, and documentation. It collaborates across marketing and business development teams to improve prospecting, relationship management, cross-selling, client acquisition, and retention.

Analyze complex datasets using graph and network analysis, identify relationships and anomalies, build dashboards, and translate findings into executive briefings and recommendations. Coordinate contractor, government, and technical teams, track milestones, manage action items, and resolve operational bottlenecks for a high-visibility Department of Defense initiative.

Analyzes and manages large-scale performance and test data for HQ CCC. Responsibilities include statistical analysis, data pipelines, dashboards, database and system administration, data governance, lifecycle management, quality controls, and stewardship. The role uses Palantir Foundry, Databricks, Power BI, Tableau, Python, R, SQL, YAML, and PySpark to deliver secure, trustworthy, auditable insights supporting cyberspace performance and risk decisions.

The Data Analyst will provide data solutions, build data pipelines, develop visualizations, ensure data integrity, and stay updated on analytics trends for a Department of War client.

Build predictive models and analytics engineering workflows for Talent Acquisition, including pipeline forecasting, candidate conversion, time-to-fill, and quality-of-hire analysis. Define strategic recruiting metrics, evaluate AI tools for ROI and bias, improve data pipelines, and lead dashboard and visualization strategy using enterprise BI tools. Partner with TA leadership, data warehouse engineers, and People teams to deliver actionable insights and resolve complex data issues.

Build and maintain Power BI dashboards, reports, data models, datasets, dataflows, security, and refresh schedules. Conduct SQL, Power BI, Excel, and Power Query analyses; partner with IT on enterprise data modeling; document data assets and methodologies; translate stakeholder needs into technical requirements; communicate findings; and coach staff in data literacy and dashboard interpretation.

Analyze complex data and develop managed data solutions, business intelligence tools, dashboards, metrics, and self-service capabilities. Partner with business and technology teams to deliver strategic insights, manage data quality, metadata, lineage, security, and access governance. The role requires scripting, querying, visualization, Snowflake development, and familiarity with cloud services and data governance.

Performs dataset evaluations and assessments to support government decision-making; develops data engineering approaches, identifies data and analytical gaps, and collaborates with software engineers to validate application changes. Provides subject matter expertise to end users, documents repeatable analytic processes, and communicates findings to government officials. The role requires expertise in technical telemetry and telecommunications data, scripting, geospatial analysis, and intelligence-focused analytics.

Own marketing performance analytics across Coalition’s insurance and cybersecurity businesses. Analyze funnels, campaigns, attribution, pipeline, and revenue; synthesize data from CRM, marketing automation, advertising, web analytics, and sales systems; develop measurement frameworks and dashboards; identify actionable recommendations; and present analytical narratives to marketing and executive leadership while partnering with data, sales, and marketing operations teams.

Performs client-facing data analysis across structured and unstructured sources, producing reports, dashboards, summaries, and actionable recommendations. Collects, validates, catalogs, transforms, and retrieves data while supporting data pipelines, warehousing, database entry, and ad hoc analysis. Collaborates with stakeholders and clients to understand requirements and translate findings into technology and business insights.

Supports data analytics, reporting, research, process improvement, and special projects. The intern collaborates cross-functionally, researches trends and best practices, and gains experience using data to support business decisions in financial services.

Performs data acquisition, quality assessments, governance reviews, compliance audits, and mission-focused analysis supporting U.S. Cyber Command. Evaluates pipelines, metadata, access controls, platforms, and security settings; develops findings, risk assessments, and recommendations; tracks remediation; maintains data lineage and governance documentation; and supports source onboarding. Collaborates with engineers, cybersecurity personnel, administrators, and government stakeholders to improve data availability, integrity, traceability, and operational decision-making.

Supports Comcast Global Audit by analyzing complex business data, developing dashboards and monitoring metrics, designing scalable data solutions, and automating audit processes. Performs ETL, statistical modeling, visualization, compliance analysis, testing, and documentation using a broad analytics technology stack. Partners with audit stakeholders, communicates findings, maintains automated production processes, and assists with AI audit initiatives. The role requires independent judgment, mentoring of less experienced analysts, and up to 20% travel.

Lead validation of enterprise-wide analytical tools for risk management: plan and execute validation projects, assess methodology quality and tool risk, prototype best practices, communicate findings, and coach junior staff.

Own monetization analytics across mobile apps and web properties, including subscription, advertising, in-app purchase, and partner-offer revenue. Build reliable datasets and pipelines, manage revenue metrics, analyze pricing and paywall experiments, model LTV and cohorts, evaluate ad monetization, reconcile revenue sources, and support forecasting and prioritization. Communicate insights to Monetization, Product, and business leaders to drive revenue growth and measurable impact.

Own user acquisition analytics across mobile apps and web properties, measuring channel performance, attribution, retention, LTV, ROAS, and payback. Build datasets, pipelines, dashboards, cohort analyses, and predictive models; reconcile MMP, ad network, and internal data; investigate anomalies and fraud; analyze funnels; design incrementality and A/B tests; and recommend budget allocation and channel strategies to the UA team.

Own analytics for cart, checkout, returns, exchanges, and accounts. Design experiments, apply causal inference, diagnose funnel issues, build KPI dashboards, maintain Python and SQL pipelines, and use AI-assisted workflows. Partner with Product, Engineering, and Design to prioritize opportunities and communicate evidence-based recommendations. The role requires strong statistical rigor, technical independence, and comfort with ambiguity in a fast-moving e-commerce environment.

Develops marketing dashboards, reports, and measurement capabilities to analyze customer behavior, campaigns, promotions, media, and demand. Uses SQL, BI tools, segmentation, forecasting, scenario modeling, and media mix modeling to optimize marketing spend and improve conversion, loyalty, revenue, and ROI. Collaborates with marketing leadership and cross-functional stakeholders to deliver actionable insights, automate KPIs, and support strategic planning.