Top Data & Analytics Jobs

Collects, validates, and analyzes operational, logistics, readiness, inventory, and supply-chain data. Leads statistical, trend, causal, predictive, and prescriptive analysis; develops dashboards, reports, scorecards, and executive briefings; supports data integration, system testing, process improvement, KPIs, and strategic decision-making. Collaborates with Army, logistics, procurement, and program stakeholders to improve medical materiel visibility, asset accountability, and supply-chain responsiveness.

Leads the design, development, migration, and deployment of scalable data pipelines and cloud data solutions. Establishes reusable ingestion, transformation, quality, governance, compliance, and orchestration processes. Partners with business and BI stakeholders to define data requirements, support financial and operational reporting, and enable AI use cases. Requires expertise in cloud and big data technologies, DevOps, CI/CD, data management, and governance, with preferred experience in Databricks, Snowflake, data warehousing, and finance-domain data.

Build and optimize Palantir Foundry applications, scalable data pipelines, ingestion workflows, data models, and ontology-aligned structures. Develop mission-focused analytics, dashboards, and operational workflows for Army decision-making. Lead technical workshops, stakeholder requirements gathering, code reviews, repository management, deployment strategies, and DevSecOps practices. Integrate AI and machine learning models while ensuring secure, compliant, and maintainable solutions.

Conduct quantitative research on trading signals, alpha, features, market microstructure, execution quality, and options pricing. Design, backtest, validate, and deploy models for automated trading strategies. Collaborate with traders and engineers to implement research in production, use AI tools to accelerate analysis, and contribute to data pipelines, evaluation frameworks, and reproducibility infrastructure.

Analyzes mission, business, data, reporting, and AI requirements; defines KPIs, workflows, business rules, user stories, and acceptance criteria. Prioritizes AI use cases, supports data architecture and BI requirements, coordinates user acceptance testing, maintains traceability, evaluates AI outputs and safeguards, and measures mission impact. Collaborates with Government stakeholders, technical teams, and Agile delivery teams while presenting findings and recommendations.

Leads the enterprise business intelligence and analytics strategy, roadmap, reporting, dashboards, KPI frameworks, predictive analytics, data governance, and responsible AI practices. Advises executives, oversees analytics delivery and team development, strengthens data quality and self-service reporting, manages priorities and vendors, and drives cross-functional adoption of data-informed decision-making across the credit union.

Leads growth analytics strategy and a multidisciplinary technical team spanning data science, engineering, business intelligence, and marketing analytics operations. Owns marketing-to-sales measurement, attribution, funnel intelligence, data strategy, MarTech integrations, AI-enabled analytics, and revenue optimization. Partners with marketing, sales, finance, and go-to-market leaders to improve demand generation, pipeline conversion, and sales outcomes while guiding technical standards, team development, vendor relationships, and analytics delivery.

Leads global consumer, market, competitive intelligence, and analytics initiatives. Translates complex data into recommendations for brand strategy, innovation, pricing, marketing, investment, and business planning. Oversees marketing measurement, ROI, brand health tracking, advanced analytics, governance, AI-enabled analytics, and external research partnerships. Influences senior stakeholders across functions and regions while building scalable insights and analytics capabilities.

Business Intelligence Intern supporting data collection, analysis, modeling, dashboard development, KPI reporting, data visualization, data quality audits, and process improvements. The role collaborates with cross-functional teams to deliver actionable insights and recommendations while developing skills in SQL, Power BI, Tableau, Excel, Python, and AI or machine learning applications.

Leads advanced quantitative research, institutional evaluation, and statistical analysis of college performance and student outcomes. Advises faculty, staff, and leaders on research design, evidence interpretation, data literacy, and responsible data use. Develops visualizations, communicates complex findings, supports strategic planning, and manages complex analytical projects involving multiple stakeholders and deadlines.

The Senior Data Analyst analyzes commercial contracting, pricing, rebate, chargeback, customer, and government pricing data to produce insights, dashboards, KPIs, and reports. The role supports data governance, quality validation, documentation, root-cause analysis, automation, AI enablement, and enterprise data management. Responsibilities include defining requirements, testing and validating solutions, improving processes, and partnering with business, project, product, technology, and external teams across the commercial contracting ecosystem.

Provides strategic direction for enterprise data engineering environments, platforms, architecture, and technology roadmaps. Leads data technology portfolios, solution design, standards, and implementation while aligning systems with business strategy. Oversees data engineering teams, researches emerging technologies, manages technical projects, and partners with IT and business stakeholders. Establishes a collaborative, performance-driven team culture and supports employee development.

Develop and maintain data pipelines, workflows, and applications that organize structured and unstructured data for reporting and analytics. Build scalable ETL/ELT solutions, retrieve and process data, and collaborate with analysts, developers, engineers, and data consumers in an agile environment. The role also involves assessing, designing, building, and maintaining analytic solutions for mission-driven clients.

Analyze complex datasets to identify trends, risks, and opportunities; develop reports, dashboards, and scorecards; perform ad hoc and advanced analytics; manage data extraction, transformation, validation, and governance; design and measure business initiatives; and present actionable recommendations to stakeholders and leadership.

Leads data and analytics strategy, delivery teams, and multidisciplinary data engineering functions across architecture, analytics, and governance. Develops people, drives business use cases, improves data ecosystem reliability, and partners with technology owners and business stakeholders. Requires strong modern data architecture knowledge, experience leading data and AI teams, and executive communication skills. Preferred experience includes machine learning, scalable cloud-native solutions, infrastructure as code, Agile practices, cybersecurity, and aerospace compliance.

Lead Client Legal Services analytics strategy and team development. Own Power BI reporting products, Microsoft Fabric data solutions, governance, predictive modeling, responsible AI adoption, ROI measurement, and executive insights. Partner cross-functionally to improve legal operations, litigation outcomes, staffing, capacity, cost management, quality, and workflow optimization while building scalable analytics capabilities and institutional knowledge.

Collects, cleans, transforms, and analyzes structured and unstructured data; builds basic statistical and machine learning models; creates dashboards and visualizations; documents data processes and findings; and supports data-driven decisions while developing foundational analytics and data science skills.

Develops data acquisition strategies, integrations, migrations, workflows, architectures, and data management procedures. Builds and maintains data pipelines, ensures data quality and security, supports cloud and healthcare claims data environments, and prepares data for analytics, machine learning, and predictive modeling. Collaborates with business and technical stakeholders to define data standards, requirements, monitoring capabilities, and process improvements.

Architects data models, curated datasets, integration patterns, and research data platforms across laboratory systems and analytical tools. Establishes data quality, lineage, metadata, catalog, and master data standards; supports LIMS and ELN architecture using platforms such as Sapio, Benchling, and Dotmatics. Leads PES roadmaps under SAFe, partners with Research IT and functional teams, mentors scientists and developers, and develops database capabilities and machine-learning data curation solutions.

Leads Odyssey’s enterprise data governance program, including federated stewardship, master data standards, systems of record, metadata cataloging, lineage, classification, data quality, business glossaries, KPI certification, AI/ML governance, compliance, and retention. Manages a team of 4–6 professionals and partners with business, engineering, security, legal, BI, and data science leaders to establish reliable, compliant, and AI-ready data practices across the organization.

Analyzes large and complex datasets to develop metrics, dashboards, reports, forecasts, statistical models, and actionable business recommendations. Supports strategic and operational decision-making, conducts scenario and machine learning analyses, and uses AI tools to automate recurring analytics. Collaborates with Marketing, Finance, Operations, product teams, and business leaders to identify data-driven improvements and communicate insights clearly.

Build and maintain Tableau dashboards, reporting, and SQL queries while defining business metrics. Perform exploratory, statistical, forecasting, variance, and cohort analyses to support planning and business reviews. Collaborate with data engineering on pipelines, data quality, governance, and machine learning models. Use AI tools to improve analytical workflows and translate technical findings into business recommendations.

Leads the Data Engineering and BI team supporting Advertising Sales. Defines technical strategy, architects scalable data platforms and context layers, modernizes workflows, enables AI and agentic applications, and establishes standards for governance, reliability, security, and cost optimization. Partners with product, engineering, analytics, and business stakeholders while recruiting, mentoring, and developing engineering talent.

Monitor fraud trends in retail deposit acquisition, analyze large datasets, identify defensive gaps, and develop strategies balancing fraud losses, operational costs, and customer impact. Partner with cross-functional and technical product teams to deliver fraud prevention capabilities, present actionable insights to senior leadership, and support business growth while protecting customers.

Develops spatial, quantitative, forecasting, and predictive analytics supporting Dollar Tree’s real estate planning, site selection, market optimization, and store network strategy. Responsibilities include sales forecasting, cannibalization analysis, GIS and demographic data integration, predictive modeling, dashboard development, workflow automation, and executive reporting. Partners with Real Estate, Finance, Operations, GIS, and senior leadership to identify growth opportunities and improve store placement and network performance.