Top Data & Analytics Jobs

Reviews and validates autonomous vehicle test-drive data for completeness, accuracy, and relevance. Identifies anomalies, supports data annotation and labeling for machine learning, develops automation scripts for verification, documents quality standards, reports data quality metrics, and collaborates with engineering teams to improve collection methods and verification workflows.

Supports Mission Partner Affiliation Sponsor activities through database development and maintenance, stakeholder coordination, data validation, recurring and ad hoc reporting, research, process evaluation, documentation, training, and day-to-day operational support. The role requires knowledge of HSPD-12 and credentialing and access management processes, independent functional work, and the ability to obtain required federal suitability or security determinations.

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.

Designs and manages Qualtrics in-product intercept surveys, targeting workflows, directories, and data collection. Analyzes user behavior, product performance, and survey feedback; builds dashboards and communicates actionable insights to product, UX, and leadership teams. Collaborates with qualitative researchers, data engineering, and development teams to integrate survey data with behavioral analytics platforms and enable access to behavioral datasets across B2B and B2C products.

Leads the creation and scaling of Unitek Learning’s enterprise analytics organization. Defines the operating model, technology stack, analytics roadmap, governance, and reporting capabilities. Oversees campus, competitive, marketplace, and macroeconomic analytics to support forecasting and strategic decisions. Partners with Finance, Operations, and Marketing, while presenting actionable insights to executive leadership and promoting data-driven decision-making and AI adoption.

Designs and manages data integrations, mappings, transformation rules, business rules, and documentation across advancement systems. Partners with business and technical stakeholders to define requirements, troubleshoot integration failures, support migrations and system enhancements, and improve data quality and governance. Develops user stories, use cases, and functional specifications while serving as the authoritative resource for integration documentation and data mappings.

Analyze, clean, validate, and transform data from multiple sources; build Kibana dashboards and visualizations; maintain data pipelines and self-service analytics assets; document data models and workflows; and translate findings into actionable recommendations for technical and non-technical stakeholders.

Supports enterprise data migration initiatives across ERP and system modernization programs. Responsibilities include source-data analysis, cleansing, mapping, transformation, reconciliation, testing, migration execution, defect resolution, reporting, and stakeholder coordination. The role partners with business, technical, and consulting teams to ensure data quality, compliance, and operational readiness throughout mock loads, cutovers, and production deployments.

Manages customer master data governance, including policies, standards, controls, data quality rules, cleansing, stewardship, KPIs, and issue resolution. Coordinates business, IT, data stewards, analysts, vendors, and technical partners; oversees master data systems; improves governance workflows and operating models; develops staff; supports roadmap execution, audits, change management, and enterprise value measurement.

Own the architecture of scientific data discovery and access across catalogs, search, federated GraphQL, application data services, and event-driven pipelines. Define schemas, contracts, service boundaries, modernization paths, performance targets, and governance controls for AI and application consumers. Partner closely with engineering on implementation, recovery and backfill, integrations, decision records, and proof-of-concept development across cloud, hybrid, and on-premises environments.