Top Data & Analytics Jobs

Leads advanced analytics, predictive modeling, survey research, program evaluation, and career-outcomes analysis for university strategic initiatives. Develops statistical models, integrates complex datasets, builds executive dashboards, and translates findings into reports, policy recommendations, and data stories. Collaborates with academic and administrative stakeholders to evaluate student success, academic programs, work-based learning, and institutional effectiveness.

Leads end-to-end business intelligence and analytics development using Power BI, including dashboards, reporting, data integration, and commercial performance analysis. Partners with cross-functional leaders to deliver insights on market share, pricing, demand, inventory, customer targeting, and competitor activity. Evaluates and implements AI and machine learning tools, manages analytics vendors, oversees ELT and data integration, resolves data issues, trains users, and presents recommendations to senior leadership.

Leads enterprise advanced analytics and modeling to identify drivers of business performance across brands, markets, customers, accounts, and geographies. Translates findings into prioritized actions, playbooks, launch strategies, and scenario-based recommendations. Oversees rigorous, scalable analytical approaches, partners with senior stakeholders, and develops analytics talent across the organization.

Leads business intelligence and analytics for Razorback Athletics’ external and revenue-generating operations. Integrates fan, donor, and commercial data to identify revenue opportunities, improve performance, and support strategic decisions. Develops analytics strategies, KPI frameworks, dashboards, and reporting systems while applying automation, predictive analytics, artificial intelligence, and machine learning. Collaborates with athletic department leaders across ticketing, fundraising, marketing, licensing, merchandising, partnerships, and concessions.

Leads the enterprise Master Data Governance program, establishing policies, standards, operating models, data-quality controls, stewardship practices, and governance roadmaps. Builds and manages data governance teams, drives cross-functional adoption, oversees master data domains and products, develops KPIs, and advances AI enablement and operational excellence across data-intensive processes.

Collect, clean, transform, validate, and model structured and unstructured data. Build and maintain reliable datasets and analytics pipelines, apply foundational data mining, NLP, and machine learning techniques, troubleshoot workflows, visualize findings, and support senior data scientists with data-quality governance and automated reporting.

Lead statistical measurement and client intelligence initiatives using healthcare, prescription, and claims data. Develop performance benchmarks, evaluate program impact, apply statistical and machine learning methods, advise data scientists, support survey-based measurement, manage analytics vendors, mentor analysts, and present findings to marketing teams and clients. The role requires advanced SQL and Python, healthcare data expertise, vendor management, and extensive quantitative experience.

Build scalable data pipelines, architectures, and analytics-ready foundations using Databricks, Python, SQL, and enterprise manufacturing data. Translate stakeholder needs into technical solutions, develop web applications, implement agentic AI and machine learning workflows, and support automation across pharmaceutical supply chain operations. The role also includes architecture collaboration, GitHub-based development, documentation, user enablement, and contributions to data strategy and digital transformation.

Manages enterprise databases, data repositories, reporting systems, dashboards, and business intelligence tools for NSWC Crane. Responsibilities include database administration, data governance, data quality, systems configuration, reporting, statistical analysis, technical documentation, user training, and support for data science and machine learning initiatives. The role develops data models, business systems analyses, automated workflows, performance reports, and recommendations while collaborating with stakeholders to improve data-driven decision-making and operational efficiency.

Research and develop high- to mid-frequency trading strategies using market data, machine learning, and market microstructure analysis. Build exchange simulators, alpha-generation tools, post-trade monitoring systems, and performance analyses for ultra-low-latency strategies. The role requires designing, implementing, calibrating, and deploying quantitative trading strategies while analyzing latency, profitability, and competitiveness. Employees must work onsite at least three days per week.

Leads the design and implementation of data architecture solutions for big data analytics and national security missions. Responsibilities include designing databases and cloud components, resolving architecture issues, guiding technical teams, collaborating with stakeholders, defining requirements, and ensuring solution delivery. The role also establishes data practices and supports analytics, machine learning, artificial intelligence, and enterprise data management initiatives.

Own and advance the enterprise commercial data strategy across Sales, Insights & Analytics, Customer Experience, and related functions. Develop the data roadmap, evaluate and govern syndicated, retail, shopper, brand, and e-commerce data assets, and manage vendor contracts and performance. Lead data quality, regional support, and cross-functional alignment while piloting AI and machine learning capabilities for commercial data workflows.

Analyzes and transforms complex financial and operational data using SQL and Python; integrates, cleans, validates, and models datasets; develops Power BI dashboards and executive reports; supports data governance, quality assurance, federal compliance, and financial decision-making. The role also leads client meetings, documents action items, develops training materials, and supports federal financial management transformation initiatives.

Leads Anovo’s enterprise data, analytics, and AI strategy, including AWS and PostgreSQL architecture, governance, data quality, reporting, predictive analytics, and responsible AI. Oversees data engineering, architecture, analytics, and data science teams; manages budgets, vendors, roadmaps, and investments. Partners with executives to define KPIs, improve patient and client outcomes, enhance operational and financial performance, and deliver governed dashboards, data products, and actionable insights.

Leads category and innovation analytics intelligence for global business planning and performance routines. Delivers insights for business reviews, identifies growth opportunities, improves analytics tools and workflows, drives adoption, ensures data integrity, and influences senior stakeholders across marketing, commercial, finance, strategy, and technology. Requires strong data storytelling, category analytics, advanced analytics, collaboration, and stakeholder management experience in FMCG environments.

Leads DePauw University's advancement technology, CRM transformation, data strategy, business intelligence, analytics, AI adoption, governance, prospect development, gift administration, and financial operations. The role oversees CRM implementation and migration, process redesign, integrations, reporting, predictive modeling, data quality, vendor relationships, cross-functional initiatives, and a multidisciplinary team supporting fundraising and alumni engagement.

Analyze exchange datasets across equities, FX, options, and futures; develop liquidity and order-book metrics; and create commercial, client-ready data products. Apply statistical and machine learning methods to identify patterns, anomalies, and predictive signals. Partner with engineering, sales, marketing, internal teams, and clients on data ingestion, normalization, cloud distribution, product specifications, competitive analysis, and market-data commercialization.

Leads a team of Operations Analysts delivering dashboards, reporting, governed datasets, process improvements, and actionable insights across Global Operations. Establishes priorities, standards, and accountability while integrating AI, automation, and predictive analytics into operational workflows. Partners with cross-functional stakeholders to identify use cases, improve data quality, manage change, and support executive decision-making across supply chain, manufacturing, logistics, and semiconductor operations.

Develops and maintains enterprise dashboards, scorecards, reporting solutions, data models, and analytics for leadership and business stakeholders. Analyzes data from IWMS, EHS, SAP, and other systems; monitors data quality; identifies trends and risks; and supports AI, automation, predictive analytics, and digital transformation initiatives. Partners with cross-functional teams, gathers requirements, trains users, governs reporting standards, and recommends improvements to operational performance and decision-making.

Lead and grow Stash’s Data Engineering team while owning the AWS data platform roadmap. Improve reliability, observability, incident response, automation, CI/CD, infrastructure as code, data quality, security, and cost management. Guide ingestion, distributed processing, storage, warehouse delivery, and real-time pipelines. Partner with engineering, SRE, analytics, data science, and business stakeholders to establish ownership, reliable data contracts, and maintainable architecture.

Leads data analytics and insights initiatives, partnering with stakeholders to answer strategic business questions through structured analysis, data storytelling, and visualizations. Builds cross-functional relationships, develops executive presentations, coaches analysts, manages complex projects, and influences business roadmaps. Uses SQL or Python to transform large datasets and applies Tableau, Power BI, and AI technologies—including machine learning, NLP, and generative AI—to solve complex business problems.

Leads enterprise data architecture strategy, roadmap, and implementation across data models, pipelines, lakes, warehouses, and business intelligence. Establishes governance, quality, security, and compliance standards; evaluates emerging technologies; collaborates with business and IT stakeholders; mentors data professionals; resolves complex data challenges; and maintains architecture documentation.

Develop and deploy scalable data pipelines and platforms that organize structured and unstructured data for mission-driven client projects. Collaborate with analysts, developers, data scientists, infrastructure engineers, and data consumers in agile environments. Support data platform assessment, design, development, maintenance, ETL operations, analytics workloads, and data examination. The role requires Python, database, source control, automation, and operating-system knowledge, plus a Secret clearance and bachelor’s degree.

Manage enterprise metadata, business glossaries, data catalogs, and end-to-end data lineage for a federal case management modernization program. Configure governance and metadata platforms, integrate data sources and pipelines, establish standards and workflows, monitor metadata quality, support compliant data sharing, develop governance metrics, document procedures, and train data stewards and business users.

Develop and maintain BI dashboards and ETL pipelines, transform and integrate structured and unstructured data, build analytical models and forecasts, apply machine learning and distributed computing (Databricks/Spark), create actionable visualizations (Qlik/Tableau/Power BI), and present insights to leadership while working in a cleared defense environment.