Top Data & Analytics Jobs

Analyzes AML and KYC data, builds regulatory reporting dashboards, develops KPIs and KRIs, identifies compliance risks and trends, improves processes and reporting, and advises leadership and business units. The role manages complex datasets, supports AML program health analysis, collaborates across teams, and contributes to projects involving data quality, operational efficiency, and compliance risk management.

Analyze complex business and customer-resolution problems, translate data requirements into product features, identify AI and GenAI opportunities, interpret analytical outputs, and communicate actionable recommendations. The role partners with technology, product, and business teams to improve complaint resolution workflows and platform adoption. Candidates need a quantitative bachelor’s degree, at least two years of relevant experience, and preferably Python, R, SQL, relational database, statistical modeling, and financial services experience.

Analyze complex business and customer-resolution problems, translate data requirements into product features, and identify opportunities to apply AI and generative AI. Partner with technology, product, and business teams to improve workflows, interpret analytical outputs, communicate insights to leadership, and support adoption of the Customer Navigator platform.

Analyze and forecast consumer credit performance for Capital One’s card portfolio. Develop risk models, test hypotheses, identify business opportunities, and provide strategic recommendations to senior leaders. Support lending product, pricing, marketing, and customer experience strategies through quantitative analysis. Lead solution development, implementation, monitoring plans, and cross-functional initiatives with IT, Sales, Operations, and Finance teams.

Develop analytical portfolio management strategies for commercial loans, balancing credit risk and profitability. Build scenario models, risk frameworks, and analytical products; monitor macroeconomic and customer credit trends; define business requirements; and oversee multiple projects and programs. Partner with executives and Product, Technology, Underwriting, Credit, and Sales teams to improve portfolio performance. The role requires strong quantitative analysis, strategic judgment, executive communication, and the ability to lead execution in a dynamic environment.

Leads compliance risk data analytics and testing strategy, plans and executes analytical projects, evaluates analytical tools, prototypes emerging practices, and translates technical findings for legal, compliance, risk, and executive stakeholders. The role also includes cross-functional partnership, written and verbal communication, and coaching and mentoring junior staff.

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.