Data Analyst

• Own Foley's enterprise data model
• Drive the medallion architecture from a product definition perspective
• Own Silver and Gold layer data definitions
• Prioritize the engineering backlog in partnership with the VP of Engineering
• Be the primary data platform partner for business stakeholders
• Own stakeholder communication
• Maintain a weekly touchpoint with the AI Value Creation Office
• Own delivery against quarterly KRs
• Own the product roadmap for Foley's intelligence self-service platform
• Own the API layer as a product
• Define and maintain the metric layer
• Partner with the data analyst and engineering to enable self-service intelligence
• Drive platform adoption and capability enablement across the organization
• Own the capabilities and paved paths backlog

Staff Product Manager, Data & Analytics

• Act as a main point of contact for business users seeking data for analytics, reporting, or operational decisions
• Guide customers on what data exists, where it resides, and how to access it across enterprise platforms
• Translate business questions into data solutions and recommend appropriate datasets or data products
• Educate users on data definitions, appropriate usage, and limitations
• Support users in navigating data catalogs and semantic layers
• Promote adoption of the Digital Brain and associated data standards
• Guide users toward certified, governed data sources vs. shadow or siloed data
• Work closely with data engineering, data quality, and platform teams to stay aligned on available data assets
• Feed recurring business needs into data product development and prioritization
• Support intake processes by helping shape business requests into structured data requirements

Lead Analyst, Data Advisor

• Act as a main point of contact for business users seeking data for analytics, reporting, or operational decisions.
• Guide customers on what data exists, where it resides, and how to access it across enterprise platforms.
• Translate business questions into data solutions and recommend appropriate datasets or data products.
• Educate users on data definitions, appropriate usage, and limitations.
• Support users in navigating data catalogs and semantic layers.
• Promote adoption of the Digital Brain and associated data standards.
• Guide users toward certified, governed data sources vs. shadow or siloed data.
• Work closely with data engineering, data quality, and platform teams to stay aligned on available data assets.
• Feed recurring business needs into data product development and prioritization.
• Support intake processes by helping shape business requests into structured data requirements.

• Lead the design, review, and approval of enterprise‑wide macroeconomic projections and stress scenarios supporting regulatory and internal use cases, including CCAR, CECL, IFRS‑9 and internal forecasting
• Assess emerging macroeconomic, geopolitical, and financial market risks and identify implications for capital adequacy, credit risk, liquidity, and earnings
• Provide thought leadership on evolving economic conditions and risks to the baseline outlook through executive‑level presentations, written briefings, and recurring senior‑leadership forums
• Collaborate with a high‑performing team of economists and analysts, fostering strong analytical rigor, clear communication, and effective challenge
• Advance the use of quantitative methods, data automation, and emerging technologies (including AI/ML where appropriate) to enhance scenario design, monitoring, and risk insights

Senior Quantitative Finance Analyst

• Translate business needs and priorities to build analytical plans that answer business questions by providing actionable insights
• Effectively communicating advanced analytics to stakeholders to inform business decisions
• Communicate & collaborate effectively with cross functional teams with competencies in market research, forecasting, commercial analytics, data science, customer engagement, data strategy, population health, competitive insights, marketing operations, medical & clinical backgrounds
• Analyze data across disparate databases/sources (including claims/EMR, DDD, and other sources) to develop insights that inform commercial business strategies
• Stay current with industry trends and advancements in analytical methodologies to bring new ideas forward (including application of GenAI) that will enhance analytic capabilities of the organization
• Contribute to innovative experiments, specifically to idea generation, idea incubation and/or experimentation, identifying tangible and measurable criteria to make meaningful improvements to the business processes and strategies
• Derive actionable business insights from various data sources, develop clear data story, and communicate effectively to business stakeholders
• Lead and mentor a team of data scientists and business analysts (on-shore and off-shore), providing guidance on best practices in data analytics, modeling and data visualization, through the scope of a project

Associate Director, US Market Engagement, Data Science & Advanced Analytics

• support ECO by helping to build and enhance data-driven solutions with a focus on critical-to-compliance risk areas
• partner with IDEAS team members and ECO stakeholders to understand business needs, translate them into technical requirements, and deliver well-tested solutions
• evaluate data using analytical and logical reasoning for the discovery of insights
• contribute to projects from concept to deployment, including requirements gathering, development, testing, and documentation

Senior Compliance Data Analyst – AI

• Delivering quarterly data reviews on schedule: identify trends, anomalies, emerging patterns, and quality issues for multiple carriers, across multiple lines of business, using our analytics platform.
• Be responsible for the relationship with multiple carriers, advancing the value proposition of our data service to increase the volume of usable data contributed to us.
• Collaborate with, and present to, internal stakeholders to ensure widespread access to and understanding of our core data assets, as well as emerging industry trends.
• Utilize your understanding of data analysis, data science, and data governance to develop automated and efficient ways to improve data quality and error detection.
• Develop in-depth understanding of insurance coverages, actuarial concepts, analytic models, information quality control, and data governance

• Lead the development, governance, and continuous improvement of global supply chain reporting and analytics frameworks
• Translate business and transformation priorities into clear analytics requirements and performance metrics
• Partner with digital and/or technology organization to automate reporting processes
• Ensure data integrity, consistency, and standardization across reporting solutions
• Drive adoption of analytics tools and reporting solutions through stakeholder engagement
• Identify trends, risks, and opportunities across supply chain operations and communicate insights clearly to senior leadership
• Contribute to the roadmap for analytics enablement, including process improvements, automation, and scalability of reporting capabilities

Manager, Reporting – Analytics

• Lead the development, governance, and continuous improvement of global supply chain reporting and analytics frameworks to support strategic and operational decision-making.
• Translate business and transformation priorities into clear analytics requirements and performance metrics aligned to Global Supply Chain objectives.
• Partner with digital and/or technology organization to automate reporting processes and enhance data compilation and visualization capabilities.
• Ensure data integrity, consistency, and standardization across reporting solutions by establishing governance, controls, and best practices.
• Drive adoption of analytics tools and reporting solutions through stakeholder engagement, training, and change management support.
• Identify trends, risks, and opportunities across supply chain operations and communicate insights clearly to senior leadership.
• Contribute to the roadmap for analytics enablement, including process improvements, automation, and scalability of reporting capabilities.

Manager, Reporting & Analytics

• May manage or supervise a small group.
• Proactively monitor and remediate incoming data used in risk measurement and reporting.
• Ensure the completeness, validity, and accuracy of data on a daily basis.
• Work with business data users to define the use of data within risk systems.
• Work closely with technology to ensure the timely and accurate operation of risk models and reporting systems.
• Implement effective risk controls of our data processes and systems.
• Participate in user acceptance testing of data control processes.
• Work with other groups as needed, including Middle Office, Sales and Trading, Technology, Compliance, Operational Risk, and Enterprise Capital Management to ensure effective controls over data for GMRM.
• Establish and maintain compliance with the Enterprise Data Management Standards related to:
• Work with report preparers to document, update and maintain end user (EUC) computing lineage for existing and new Risk Data Aggregation (RDA) reports
• Integration (stitching) and sustainment of EUC and technical PDE data lineage from the report back to one hop outside of Credit Risk
• Maintaining EUC lineage in Enterprise tools (DQC Toolkit)
• Performing quality assurance analysis on data lineage
• Updating asset flow diagrams
• Facilitate validation that the inputs into the Critical Risk Figures (CRFs) are fit-for-purpose including analysis of discrepancies, tracking and coordinating remediation efforts
• Track and report on status of project deliverables

Senior Data Support Analyst

• Design, build, and maintain the reporting infrastructure used to manage utility energy efficiency programs.
• Develop recurring dashboards, scorecards, KPI reports, and executive summaries that provide visibility into program performance.
• Create and maintain Power BI dashboards and reporting tools that support operational and strategic decision-making.
• Identify opportunities to improve reporting automation, efficiency, and usability.
• Document reporting methodologies, calculations, and data sources to ensure long-term sustainability.
• Consolidate and reconcile data from multiple sources, including program tracking systems, Excel-based databases, SharePoint, Power BI, and operational platforms.
• Analyze program performance data to identify trends, risks, bottlenecks, and improvement opportunities.
• Proactively communicate insights and recommendations to program leadership.
• Support forecasting, planning, and performance monitoring activities.
• Translate complex data into clear, actionable information for both technical and non-technical audiences.
• Partner with Program Managers, Operations Managers, and Engagement Managers to define reporting requirements and performance visibility needs.
• Support quality assurance and data validation efforts to ensure reporting accuracy.
• Assist with client reporting, regulatory reporting, and internal performance reviews.
• Contribute to process improvement initiatives through operational analysis and data-driven recommendations.
• Support special projects and strategic initiatives as assigned.

Program Reporting & Analytics Analyst – MDEA

• Performs data profiling, cleansing, validation, and reconciliation activities to improve the quality across systems
• Identify, investigate, to data discrepancies and root causes; advance challenges and support resolution
• Support in building and maintaining automated workflows to reduce manual effort and improving data
• Maintain data quality dashboards, scorecards, and Key Performance Indicators; identifying trends and improvements
• Partner with different functions and organizations within Supply chain to understand data needs and drive corrective actions
• Maintain standard operating procedures, data standards, and knowledge-base content to sustain operations

Experienced Analyst, Data Quality

• Perform data profiling, cleansing, validation, and reconciliation activities
• Identify and investigate data discrepancies and support resolution
• Build and maintain automated workflows to reduce manual effort
• Maintain data quality dashboards, scorecards, and Key Performance Indicators
• Partner with functions within the supply chain to understand data needs

Experienced Analyst – Data Quality

• Identify business intelligence and data analysis needs
• Work closely with Business and Technical teams
• Turn data into critical information for business decisions
• Engage business and development teams to design dashboards, alerts, and reports
• Provide project leadership including facilitating requirements gathering
• Conduct analysis of functional business processes
• Educate clients to use data as an analytical tool

Business Data Analyst

• Design, develop, and maintain enterprise-wide HR reports and dashboards using Workday Report Writer, Calculated Fields, Matrix/Advanced Reports, Discovery Boards, Worksheets, and scheduling
• Deliver executive-ready reports, dashboards, and presentations — translating complex workforce data into clear, concise, and immediately actionable insights
• Triage incoming reporting requests; assess requirements, scope, and prioritization; consult with stakeholders to connect data to business decisions and align on the highest-value work
• Serve as the SME for all HR reporting used internally and externally, including executive, regulatory, and operational audiences; partner with consultants on annual government filings (EEO-1 etc.)
• Champion data governance, data quality, and data accuracy; maintain the HR data dictionary and enforce standardized definitions, field usage, and calculation logic
• Perform regular reporting audits and monitor data quality across sources; proactively identify and resolve issues affecting accuracy, compliance, or user experience
• Ensure report security is maintained; navigate Workday security domains and confirm users have appropriate access consistent with data privacy requirements
• Collaborate with HRIS and IT peers on governance, security, and continuous improvement of reporting infrastructure
• Partner with the HRIS leader and Data Analytics team to develop an AI-informed HR reporting strategy — leveraging tools like Claude and MCP integrations with Workday and Adaptive to build efficient, reusable reporting workflows
• Manage and expand the organization's use of Lightdash for HR dashboard development and self-service analytics
• Evaluate the need for third-party people analytics platforms and, if adopted, own the full implementation lifecycle — requirements, data mapping, UAT, validation, and end-user enablement
• Review Workday system upgrades and releases; assess impact, conduct testing, and recommend enhancements; proactively research emerging tooling to identify adoption opportunities

Senior HR Reporting & Analytics Manager

• Working in a fast-paced, innovative, and change-oriented work environment
• Using programming skills to explore, examine and interpret large-scale data in various forms
• Determine the appropriate techniques to manipulate complex high-volume data, develop insights through analysis and modelling, evaluate business problems, and improve our analytical speed-to-insight
• Perform data mining and analyzing of structured and unstructured data associated with claims, policy, payment activities to solve complex business problems using advanced techniques and leveraging industry cutting-edge technology
• Focus on automation and utilizing technology to provide repeatable reporting solutions to promote self-service culture for business partners
• Building a strong network of peers and mentors
• Attending on-site technical and professional development classes
• Presenting accomplishments to leadership across the organization
• Participating in sponsored community service events

Data Analytics Co-Op

• Translate data into decision-ready insights — synthesize consumer, category, competitor, and macro-trend data into clear "so-what" implications that pressure-test the Wellbeing strategy.
• Build the analytical backbone for category strategy, portfolio choices, and M&A thesis work — market sizing, share/penetration, white-space, growth drivers, consumer segmentation, early signal detection, and leading indicator tracking
• Help build and scale a repeatable growth intelligence capability – mapping priority data sources, defining “metrics that matter”, pressure-testing early signals, and translating emerging insights into actionable brand, category, innovation, and M&A workstreams.
• Run structured problem solving on defined modules of strategic initiatives (e.g., category deep-dives, competitor teardowns, target screens), owning workplan, analysis, and first-draft recommendation.
• Develop board- and C-suite-ready materials — turning raw analysis into crisp slides, narratives, and one-pagers that equip senior executives for critical engagements.
• Be the team's data whiz and CMI partner — fluently using Circana, Stackline, Numerator Panel, Euromonitor, social listening, and primary research (qual + quant) to bring the consumer voice into every question.
• Pioneer trend and foresight inputs (GLP-1, science-backed claims, omnichannel discovery, AI-enabled routines, etc.) into a forward-looking view the team can act on, including M&A target screening, brand/category assessments, and competitive benchmarks across the M&A funnel.
• Run the PMO for strategic projects — M&A due diligence and AOP — owning master workplan & calendar, weekly cross-functional connects, status reporting, milestone tracking, and senior-stakeholder decks.

Strategy and Analytics Associate Manager

• Design the analytical models and metric logic the agent reasons with — contribution margin (CM3), acquisition truth (aMER, NCAC), cohort LTV/payback, ad spend efficiency and marginal-return analysis, incrementality testing (geo lifts, conversion-lift, MMM calibration) — from raw platform data to decision-ready insight.
• Define the schemas that encode marketing tradecraft: how creative, channel, financial, and customer data connect into a queryable picture of a brand.
• Own accuracy and judgment — what's load-bearing vs. noise, where attribution lies, how to compute metrics that survive operator scrutiny.
• Spec the model; partner with data eng to build the pipeline and the AI team to wire it into agent skills.
• Guide incrementality testing strategy across Darkroom's paid media programs — geo holdouts, matched-market tests, and conversion-lift studies — and run the power analysis to size tests correctly before spend is committed.
• Support MMM strategy, vendor evaluation, and model calibration where programs need it.
• Partner with Paid Media and Growth Strategy teams to design tests up front and translate results into clear, executive-ready budget recommendations.

Associate Director, Data Strategy & Analytics

• Lead the design, implementation, and evolution of scientific data products and integration strategies supporting AI-enabled drug discovery and development.
• Create scalable, interoperable, and AI-ready data products that connect discovery, preclinical, clinical, safety, and real-world evidence domains.
• Establish the data architecture, integration strategy, metadata framework, and productization approach needed to support semantic reasoning, knowledge graphs, GraphRAG, advanced analytics, and agentic AI applications.
• Define the future-state scientific data ecosystem and ensure high-quality data products are delivered to support translational science and patient safety initiatives.
• Build AI reasoning models to support data-driven translational safety decision making.
• Define and execute a scientific data product strategy supporting Discovery Research, Translational Science, Preclinical Safety, Clinical Development, Pharmacovigilance, Real-World Evidence.
• Design integration frameworks connecting heterogeneous scientific data sources and define data harmonization strategies spanning SEND, SDTM, ADaM, MedDRA, Imaging, Omics, Biomarker, Pathology, Real-world data.
• Lead design and implementation of curated datasets, semantic-ready data products, feature stores, metadata products, scientific data services, and AI-ready data assets.
• Define metadata standards and data quality frameworks, implement lineage, provenance, traceability, and FAIR data principles.

Principal Scientist, Data Science – Data Products, Integration & Analysis

• Lead the design, implementation, and evolution of scientific data products and integration strategies supporting AI-enabled drug discovery and development
• Create scalable, interoperable, and AI-ready data products connecting discovery, preclinical, clinical, safety, and real-world evidence domains
• Establish data architecture, integration strategy, metadata framework, and productization approach for semantic reasoning, knowledge graphs, GraphRAG, advanced analytics, and agentic AI applications
• Define the future-state scientific data ecosystem
• Build AI reasoning models to support data-driven translational safety decision making
• Partner with Amazon engineering and deployed platform resources to deliver scalable data pipelines and data products
• Define implementation strategy for scientific data products deployed on AWS, ensuring alignment with enterprise architecture, security, governance, and AI-readiness requirements

Data Analyst jobs in New Jersey

See all jobs on JobTailor

Staff Product Manager, Data & Analytics

Lead Analyst, Data Advisor

Lead Analyst, Data Advisor

Senior Quantitative Finance Analyst

Associate Director, US Market Engagement, Data Science & Advanced Analytics

Senior Compliance Data Analyst – AI

Data Analyst

Manager, Reporting – Analytics

Manager, Reporting & Analytics

Senior Data Support Analyst

Program Reporting & Analytics Analyst – MDEA

Experienced Analyst, Data Quality

Experienced Analyst – Data Quality

Business Data Analyst

Senior HR Reporting & Analytics Manager

Data Analytics Co-Op

Strategy and Analytics Associate Manager

Associate Director, Data Strategy & Analytics

Principal Scientist, Data Science – Data Products, Integration & Analysis

Principal Scientist, Data Science – Data Products, Integration & Analysis