Top Data & Analytics Jobs

Support Chase Card Services by delivering credit risk analytics and insights to inform portfolio decisions and product features. Analyze performance, identify trends and root causes, present recommendations to leaders, maintain risk frameworks aligned to regulations, monitor behavioral data and industry trends, and partner cross-functionally to enhance decision rules and monitoring.

Lead end-to-end delivery of governed CRM data products for CIB Sales: define requirements, ensure data quality, SLAs, documentation, and deliver reusable datasets, APIs, dashboards and ML-ready assets while partnering with stakeholders and platform teams.

Measure and improve digital acquisition and onboarding journeys through instrumentation, dashboards, alerts, funnel analysis, experimentation, and customer journey insights. Diagnose conversion, engagement, and drop-off drivers; interpret A/B/n test results; and translate findings into prioritized recommendations. Partner with product, marketing, operations, and technical stakeholders across digital, phone, and branch channels to identify friction, detect issues quickly, and guide roadmap decisions.

Provides enterprise-wide technical leadership in data engineering and architecture. The role drives adoption of modern technologies, establishes engineering practices, advises on technology platforms and capabilities, influences stakeholders, mentors engineers, recruits talent, and develops next-generation technology roadmaps. Responsibilities include data engineering, AWS application development, data modeling, big data processing, ontology standards, and machine learning model deployment.

Lead analytics for US Card: identify business opportunities, build and test models, support product/pricing and marketing, manage credit risk analysis, drive implementation, and partner with IT, Sales, Operations, and Finance.

As a Lead Data Engineer, you will collaborate with Agile teams, develop technical solutions, and enhance cloud-based data warehousing to empower financial services for customers.

Leads the Analytics and Reporting Services team supporting a Medicaid Enterprise Data Warehouse. Oversees reporting portfolio delivery, dashboards, data validation, governance, compliance, resource planning, and operational performance. Manages analysts and business intelligence professionals, translates stakeholder needs into analytics solutions, improves data quality and reporting automation, and advises government and executive stakeholders on reporting modernization and data-driven decision-making.

Lead enterprise data and analytics integration for a large home health and hospice organization. Build unified governance, resolve legacy metric conflicts, design centralized analytics organization, migrate reporting from MicroStrategy to Power BI, define enterprise data architecture, and deploy AI/ML capabilities to deliver clinical, operational, financial, and strategic insights across the Optum ecosystem.

Designs and maintains production data pipelines, dbt models, Airflow workflows, and Snowflake datasets integrating Workday and other People systems. Owns data quality, observability, governance, row-level security, and access controls for sensitive People data. Builds semantic models and AI agents, collaborates with analysts and stakeholders, translates requirements into reliable data products, communicates technical trade-offs, and mentors other engineers.

The Senior Business Operations Analyst will focus on data-driven insights and operational strategies for Collections operations. Responsibilities include SQL analysis, Tableau reporting, and collaborative optimization with various teams to enhance efficiency and decision-making.

Leads and develops a data engineering team supporting People Analytics and AI-assisted workforce analytics. Designs scalable data models, pipelines, semantic layers, testing frameworks, and governance practices. Remains hands-on with production code, reviews, and technical problem-solving while partnering with People Analytics, business, legal, and compliance stakeholders. Establishes engineering standards across Python, SQL, dbt, Airflow, Snowflake, CI/CD, data quality, observability, privacy, and security.

Perform data sourcing, cleansing, analysis, and automation to produce KPI reporting and interactive dashboards. Support stakeholders with ad hoc analyses, present insights and recommendations, provide BI platform user support, and collaborate to improve and automate reporting processes across Wealth Management.

Design, build, and optimize modular dbt pipelines and data models; translate ambiguous product requirements into production-grade data assets; diagnose query performance and lower warehouse compute costs (including migration to Snowflake); enforce code hygiene, data security, testing, and peer review; mentor junior engineers and adopt AI-assisted development tools to speed test generation and legacy discovery.

Supports marketing analytics through dashboard development, recurring and ad hoc reporting, data hygiene, database querying, statistical analysis, and actionable recommendations. Provides hands-on support for Voice of the Customer and Customer Lifetime Value programs, including survey data consolidation, response monitoring, reporting, and research-partner coordination. Manages analytics request intake, prioritization, documentation, and stakeholder communications across Marketing and eCommerce.

Support and improve enterprise Customer 360 and MDM capabilities through identity resolution, match/merge, survivorship, stewardship, data quality, and governance. Investigate ingestion and transformation issues using SQL and Snowflake, partner with business and technical stakeholders, automate stewardship and remediation workflows, and contribute to AI-enabled, scalable customer data solutions and operational utilities.

Lead the Power & Energy segment’s data architecture vision, strategy, target-state roadmap, conceptual and enterprise data modeling, governance standards, security, metadata, lineage, and solution design. Partner with data engineering, analytics, IT, business stakeholders, and executives to ensure scalable, reusable, high-quality data ecosystems aligned with business needs. Guide data modernization, cloud migration, and digital transformation initiatives.

Analyze large datasets for the Fraud and Risk team, develop dashboards and reporting structures, present insights, and support data-driven risk prevention. The role involves quantitative research, fraud detection, risk assessment, rules-based and machine learning models, and collaboration with stakeholders to solve business problems.

Analyze large datasets for the Fraud and Risk team, develop dashboards and reporting structures, present insights, and support data-driven risk prevention. The role involves quantitative research, stakeholder communication, and assisting with rules-based and machine learning models to detect fraud, assess risk, and improve compliance and security measures.

Analyze large datasets for fraud prevention and risk management, develop dashboards and reporting structures, present quantitative research, and support rules-based or machine-learning models. Collaborate with management and cross-functional stakeholders to identify business problems and implement data-driven solutions that improve risk prevention and compliance.

Own and evolve the Collibra meta-model, integrations, and workflows. Design configurations and security/lineage standards, automate workflows, coordinate changes with Pfizer Global Supply, perform risk/impact assessments, and support development/test/production environments to make trusted data discoverable and usable.