Top Data & Analytics Jobs

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.

Leads data analysis strategy for an analysis platform product, including data mining, modeling, testing, reporting, process improvement, and product analytics. Manages junior analysts, mentors team members, collaborates across business units, and supports large-scale databases and data storage systems. The role includes business intelligence, strategic experimentation, operational efficiency improvements, and consulting on production and data system design.

Leads data governance, risk mitigation, analytical tool validation, and program development for Global Payment Networks. Responsibilities include planning validation projects, assessing analytical methodologies and tool risks, researching industry practices, preparing reports and presentations, and coaching junior staff. The role requires managing concurrent projects and applying data analytics, risk management, statistical, and project management expertise to develop enterprise-wide controls and processes.

Develop, implement, govern, and integrate enterprise ontologies and data models. Harmonize linked data, establish semantic and data-standardization guidelines, support knowledge organization and machine-learning integrations, and advocate semantic technology across Finance and Enterprise teams. Use W3C ontology standards and specialized tools to test, troubleshoot, and maintain models while collaborating with Technology, Product, and Machine Learning stakeholders.

Leads enterprise ontology and data-modeling strategy, governance, integration, standardization, and roadmap development. Manages teams creating semantic models, taxonomies, linked data, and reusable capabilities while partnering with technology, machine learning, and business stakeholders. Advocates W3C standards, supports knowledge organization workshops, establishes modeling guidelines, monitors industry trends, and mentors team members. Requires expertise in metadata, ontologies, linked data tools, graph technologies, SQL or SPARQL, and semantic standards.

Develops and governs enterprise ontologies, semantic models, and data standards. Partners with Finance, Technology, Product, and Machine Learning teams to integrate semantic technologies, harmonize linked data, improve data discoverability, and support product development. Responsibilities include applying W3C standards, managing ontology tools, testing models, advocating data standardization, monitoring industry developments, and overseeing related projects.

Leads enterprise analytical tool validation, including framework refinement, project execution, methodology risk assessment, technical research, and prototyping of industry practices. Communicates findings through reports and presentations, partners with cross-functional leaders to influence strategy, and coaches junior staff. The role also manages multiple concurrent projects and evaluates statistical and econometric models, data governance, and predictive analytics approaches.

Manage data analysis for transaction monitoring, risk identification, and compliance. Analyze high-volume transaction data using SQL, Python, Splunk, and visualization tools; conduct root-cause investigations; design risk data architectures; identify process and reporting improvements; advise business and product teams; and translate technical findings into executive recommendations. The role also involves stakeholder liaison, regulatory alignment, data integrity, and managing concurrent analytical projects.

Analyze complex data to solve business problems through innovation, business intelligence, and data management. Build self-service data solutions, dashboards, metrics, and visualization tools; deliver strategic insights; and manage data quality, metadata, lineage, security, access governance, and monitoring. Collaborate with business and technology teams while using scripting languages, data platforms, and AWS services.

Analyze enterprise incentive compensation plans, performance measures, payout mechanics, and participant data to identify risks and trends. Develop quantitative models, test hypotheses, evaluate plan designs, and recommend improvements that balance business goals with prudent risk-taking. Translate complex analyses into actionable insights and presentations for senior leaders, partnering across HR, Finance, IT, Sales, and Operations to support decision-making and implementation.