Data Analyst Jobs in Jersey City, NJ

Support data management and analytics for investment strategies by ensuring accuracy and integrity of portfolio data, performing reconciliations, automating end-to-end workflows, collaborating with technology and business stakeholders, and delivering recurring analytics and reports for sales, marketing, risk, and investment teams.

Analyze data center operational practices, identify risks and inconsistencies, and create scalable enablement materials (SOPs, runbooks, templates, training). Partner with technicians, engineers, security, and compliance to validate procedures, support audit readiness, and leverage modern tooling including AI/LLM workflows to accelerate documentation and onboarding.

Perform end-to-end data analysis, profiling, validation, and transformation for large-scale P&C insurance data. Create source-to-target mappings (STTM), translate business requirements into technical specs, optimize SQL queries, and support data consolidation, standardization, and quality efforts with stakeholders and engineering teams.

Create and edit WordPress pages, improve site UX and visual design, upload reports and maintain research database. Analyze and present website data from Google Analytics to inform communications strategy. Use basic graphic design tools (Photoshop, Canva), assist with virtual events (Zoom), and apply AI tools under human oversight. Maintain accuracy in names/titles/technical terms, act quickly on priorities, and collaborate with a diverse, largely remote team. Familiarity with AWS is a plus; occasional travel for events may be required.

Verify and maintain database master and control file metadata; identify, research, and resolve data errors; generate and respond to reports; document system files and reports; recommend improvements and coordinate modifications; learn legacy source systems and perform source-to-target data mapping to support analytic data lineage.

Manage market data service delivery and client projects, handle vendor and entitlement administration, contract negotiation, procurement, invoicing and exchange reporting, oversee inventory and leavers/joiners, identify cost savings, and coordinate with internal stakeholders to meet SLAs.

The Data Analyst Intern supports AI initiatives by handling data management, exploratory analysis, AI model support, and creating visualizations to drive actionable insights.

The Claims Data Solutions Sr. Analyst ensures effective data consumer perspectives, identifies essential data elements, acts as Product Owner for data products, documents business requirements, and analyzes data sets for decision-making.

Analyze and consolidate disparate data sources, document functional and business specifications, review data models, validate implementations, support production deployment, and investigate data quality and lineage issues.

Lead requirements gathering, document functional specifications, review data models, validate implementations, support production deployments, investigate data quality and collaborate with technology teams to ensure data completeness and lineage.

Collect, consolidate, and validate data from disparate sources; document functional specifications; review data models; gather business requirements; support deployments; investigate data quality and bridge gaps with technology teams.

Lead compliance training reporting, oversight, and data management for U.S. Compliance. Develop and maintain reporting, dashboards, trackers and audit-ready documentation; validate and reconcile training data; advise business partners on regulatory training requirements; manage projects and remediation, and support regulatory readiness and program governance.

The Claims Data Quality Analyst role involves ensuring data integrity and accuracy, analyzing claims corrections, and collaborating across teams to improve data quality.

Design and implement global tax data models and governance. Translate business requirements into logical and physical models, improve data quality, build automation/workflows, resolve cross‑stakeholder data issues, and support development, testing, and production with tax and data engineering teams.

Senior Business Analyst in wealth management focused on data governance: define Key Data Elements, business rules, and data quality controls; profile and analyze data; validate lineage; translate business requirements into technical specs; lead UAT and testing; manage data quality monitoring and remediation; build cross-functional stakeholder relationships and advocate data-as-an-asset.

Support and improve the organization's data governance and GRC program by defining standards, documenting metadata and lineage, enforcing PII and retention policies, training stakeholders, monitoring data quality and compliance (CCPA), coordinating with security and engineering, conducting risk assessments and audits, automating processes with scripts, and managing incidents via ITSM systems.

Support privacy governance and regulatory compliance across the Americas by advising business units, managing privacy risk, conducting privacy impact assessments, maintaining records of processing activities, coordinating incident and forensic responses, developing policies and training, and working with Legal and Compliance to implement privacy controls for new technologies.

Support design, delivery, and enhancement of insurance data products. Elicit and document requirements, create user stories and data mappings, validate data using SQL, support data pipelines and UAT, resolve data issues, and contribute to data quality, governance, and documentation.

Serve as product-owner/business analyst for actuarial data and tools within the Global Data Office. Translate actuarial requirements into data engineering specs, lead Agile ceremonies, manage product backlog and roadmaps, align stakeholders, and ensure data governance, lineage, testing, and quality for actuarial reporting, reserving, and pricing use cases.

Lead processing of survey data into cloud analysis tools, build dashboards and visualizations, train and support clients, collaborate across teams, and deliver high-quality work to meet project objectives and deadlines.