Data Analyst

• Owns dashboards: pipeline generation, coverage, forecast, win rates, sales cycle, quota attainment, ARR, net-new vs. expansion.
• Builds Pigment models and opportunity-level datasets for pipeline, capacity, revenue.
• Analytics backbone for annual and in-year sales planning cycles.
• Designs data pipelines from Salesforce, Pigment, Gong, Netsuite, etc.
• Partners with Data Engineering on dbt/warehouse transformations.

Senior AI Data Analyst – Sales

• 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

• Design, develop, and maintain Power BI semantic models that support enterprise reporting and self-service analytics.
• Develop scalable star schemas, measures, calculated columns, hierarchies, perspectives, and Row-Level Security.
• Optimize semantic models for performance, usability, and governance.
• Build reusable metrics and governed business logic shared across reporting solutions.
• Develop and enhance analytics solutions using Microsoft Fabric Lakehouse technologies.
• Write and optimize SQL, Spark SQL, and PySpark notebooks supporting analytics workloads.
• Partner with Data Engineers to improve data quality, performance, and reliability.
• Troubleshoot data pipelines, semantic models, and reporting issues across the platform.
• Design AI-enabled analytical experiences using Microsoft Fabric Data Agents and Azure AI technologies.
• Develop structured outputs (including JSON) that support internal web applications and AI-powered user experiences.
• Evaluate emerging AI capabilities and recommend practical applications that improve productivity and business value.
• Build dashboards that monitor Fabric capacity utilization, refresh performance, workload health, pipeline execution, and overall platform performance.
• Develop reporting that helps engineering teams proactively identify performance bottlenecks and operational issues.
• Help establish monitoring standards for enterprise analytics solutions.

Senior Data Analyst

• Works closely with department roles and cross-functional study team members to create data capture solutions that support the quality and timely delivery of data
• Complies with applicable SOPs and work practices
• Learns Pfizer database technologies
• Develops knowledge of data capture tools and methods that support the accuracy and integrity of study data

Database Analyst – Clinical Data Collection Strategies

• Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
• Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
• Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
• Flex your interpersonal skills to translate the complexity of your work into tangible business goals

Senior Associate, Data Scientist – Commercial Bank Strategy & Analytics

• Design, engineer, develop, and certify enterprise data products for broad consumption across analytics, reporting, AI, and business intelligence use cases.
• Partner with Enablement & Governance teams to ensure appropriate documentation, controls, processes, and standards are incorporated throughout the data product lifecycle.
• Collaborate with Subject Matter Experts to establish business definitions, rules, metrics, and semantic layers that provide context and make data products AI- and BI-ready.
• Support the evolution of analytics by evaluating and applying emerging technologies, AI capabilities, analytical methodologies, and best practices.
• Contribute to the development of standards, playbooks, and reusable frameworks that advance enterprise analytical capabilities.
• Partner with Product Strategy leaders to evaluate the performance and effectiveness of existing product strategies and recommend opportunities for optimization.
• Analyze portfolio performance, customer behavior, engagement trends, and product outcomes to identify opportunities for growth, risk mitigation, and improved customer experience.
• Perform deep-dive analyses to understand customer journeys, behavioral patterns, and drivers of product adoption, usage, retention, and attrition.
• Identify under-engaged, over-engaged, or emerging customer segments and develop recommendations to improve targeting, strategy execution, and customer outcomes.
• Evaluate marketing, communication, servicing, and customer experience strategies to identify opportunities for enhanced effectiveness and engagement.
• Develop analytical frameworks, performance measurement methodologies, and monitoring capabilities to assess strategy outcomes and inform decision-making.
• Translate complex analytical findings into clear, actionable insights and compelling business recommendations for senior leadership and key stakeholders.
• Deliver proactive insights that influence product strategy, customer experience improvements, and enterprise growth objectives.

Client Quantitative Analyst I

• Support the Insights & Analytics team in collecting, organizing, and analyzing programmatic data to help New Classrooms better understand student outcomes and program performance
• Translate data requests from internal stakeholders into clean, well-documented analyses, and present findings in ways that are accessible to both technical and non-technical audiences
• Work alongside applied data scientists, product managers, and program leaders
• Extract, clean, and prepare data from multiple sources, to support recurring and ad hoc reporting needs
• Conduct exploratory and descriptive analyses to identify trends, patterns, and anomalies in student and program data
• Maintain and document data queries, transformation logic, and analytical workflows to support team consistency and reproducibility
• Build and maintain dashboards and reports in Metabase (or comparable BI tools such as PowerBI or Tableau) to support decision-making across the organization
• Translate analytical findings into clear, well-designed visualizations for a range of audiences, including program teams, leadership, and external partners
• Partner with colleagues across Program Success, Product, and Academic teams to understand data questions and ensure analyses are grounded in operational and programmatic context

• Conduct collision scene investigations
• Conduct vehicle examinations
• Analyze physical evidence, vehicle damage, roadway conditions, photographs, and electronic data
• Download, collect, and interpret Event Data Recorder (EDR) data
• Obtain and analyze Vehicle Sampling Evidence
• Analyze and interpret evidence and data to render an expert opinion pertaining to damage and to confirm or dispute a claim
• Work independently and manage assignments from intake through final reporting
• Maintain professional documentation and chain of custody standards
• Present findings in the courtroom as an expert

Collision Data Analyst

• Support development of project kickoff decks and study protocols
• Research and compile medical and drug code sets for EHR and claims-based studies
• Draft final study deliverable (final reports, slide decks, abstracts, posters, and manuscripts)
• Review and format descriptive statistical output tables to ensure client-readiness
• Perform quality assurance on programming output
• Track study progress, timelines, and deliverables
• Attend internal and client meetings; own meeting minutes and follow-ups
• Support scheduling and cross-team coordination

Real World Evidence Research Analytics Analyst

• Develop business strategies that will drive growth, profitability, and competitive success for Capital One
• May manage and develop 1-2 analysts, coaching and mentoring associates
• Develop and implement new product and pricing strategies for various lending products
• Lead direct-to-consumer marketing efforts and build targeted insights
• Drive improvements in credit performance via creating risk models and rigorous analysis
• Manage and sequence delivery of business intent, build business requirements, and execute product strategy
• Work closely with colleagues across Capital One including: IT, Sales, Operations, and Finance

Business Manager – Marketing, Analytics, Product Strategy

• Provide ad-hoc support to our global Sales and Sales Ops organizations to ensure accuracy of our Finance KPIs that impact revenue forecasting: ACV, ARR, Renewals
• Bridge and reconcile financial metrics, from quote lines to ACV to ARR
• Build reporting data sets and dashboards to support revenue-impacting projects or Sales initiatives
• Collaborate closely with upstream CRM platform teams to ensure high level of data quality
• Partner with Finance Data Engineering Team to investigate and drive solutions as the business evolves
• Participate in financial month-end and quarter-end close process

Financial Data Analyst

• Collaborate with Product Managers, Business Stakeholders, and Engineering teams to gather, analyze, and document business requirements
• Translate business requirements into detailed functional and technical specifications
• Define product features, acceptance criteria, user stories, and business workflows
• Analyze large datasets to identify trends, business insights, and optimization opportunities
• Work with GCP Data Engineering teams to deliver scalable analytics solutions
• Develop business dashboards and executive reports

Technical Product and Data Business Analyst, GCP Analytics

• Conduct and deliver primary research: Ensure that a modern data foundation that includes data quality, governance and context-ready data amplifies development of analytics, data science, ML, and AI internal products.
• Help clients activate, measure, and scale the use of analytics, data science, ML, and AI for business-focused outcomes and use cases.
• Drive alignment among internal stakeholders on data and analytical priorities that support business impact.
• Create approximately eight to 12 high-quality, actionable, analytically deep, and fact-based research projects per year, which include a mixture of written reports, tools, webinars, videos, blogs, podcasts, infographics, and other intellectual property.
• Work alongside sales and marketing teams to promote visibility for this research.
• Drive and lead key Forrester Wave™ and Landscape reports, which are deep, objective evaluations of the most important vendors of data, analytics, and AI technologies.
• Consult clients to apply Forrester’s research in the context of their specific business environment and help solve their problems through short-term and longer-term consultative engagements.
• Present at Forrester-sponsored and industry-related events, as well as deliver client webinars.
• Establish an industry presence as an influential speaker and thinker, build relationships with journalists who cover the sector, and participate in press inquiries as necessary.
• Support business development and prospect conversations as arranged by Forrester’s account leadership teams.
• Foster a style that drives a culture of cross-team collaboration, mentorship, integrity, and relentless and positive pursuits.

Senior Analyst, Data, Analytics and Machine Learning

• 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

• 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

• Assists in development and analysis of quantitative/econometric behavioral models used for credit risk, interest rate risk and liquidity risk management, as well as balance sheet and capital planning.
• Supports more experienced analysts and management in data analysis, model development efforts and ad-hoc analysis as needed.
• Assist in researching and developing quantitative behavioral models used for credit risk, interest rate risk and liquidity risk management, as well as balance sheet and capital planning, including but not limited to, loan delinquency, default and loss models, loan prepayment and utilization models, deposit attrition models and financial instrument valuation methods.
• Prepare, manage and analyze large customer loans and deposit data sets for statistical analysis in Structured Query Language (SQL) or similar tool to properly specify and estimate econometric models to understand customer or Bank behavior for purposes of interest rate, liquidity or stressed capital risk.
• Understand the context of the Bank's data and businesses to ensure properly developed models.
• Produce and run regressions (including time series and logistic regression), programming routines and other econometric analyses to specify models using appropriate statistical software; communicate results, including graphic and tabular forms of model development activities to fellow team members, Treasury management and Bank-wide stakeholders, including the business lines and Risk Management colleagues to demonstrate key risk drivers and dynamics of model output.
• Execute models in production environment; communicate analytical results to Bank-wide stakeholders.
• Track portfolio performance, model performance, campaign tracking and risk strategy results.
• Incorporate observations and data into existing models to improve predictive results.
• Identify deviations from forecast/expectations and explain variances.
• Identify risk and/or opportunities.
• Support development and maintenance of satisfactory model documentation, including process procedures and performance monitoring guidelines to serve as reference source.
• Provide financial analysis and data support to other groups/departments across the Bank as required.
• Engage with colleagues in Model Risk Management for model validation exercises.

Credit Model Development Quantitative Analyst I – HELOC, Residential Mortgage

• This position plays a critical role in advancing IH&S’s finance data transformation initiatives by focusing on developing and maintaining Power BI dashboards, enabling standardized financial reporting, and translating complex financial and operational data into clear, decision-ready insights.
• Building data models and creating processes for monthly, quarterly, and annual financial reporting cycles, ensuring accuracy, consistency, and timeliness of data.
• Analyze financial and operational data to identify ways to capture and report on trends, variances, risks, and opportunities, and present findings to finance leadership.
• Partner with Finance, Accounting, Commercial, IT, and Operations teams to ensure data consistency, and alignment between the tools (dashboards/reports) used for financial reporting and to monitor business performance drivers.
• Maintain and prioritize reporting and analytics backlogs leveraging the Agile framework.
• Support executive-level reporting by creating clear, concise, and visually compelling dashboards and summaries.
• Contribute to finance and business transformation initiatives, including automation of reporting processes and improvement of data accessibility and usability.
• Support various workflows by developing financial KPI calculation logic, creating PBI visuals for leadership consumption.
• Support standardized reporting frameworks and ongoing transformation initiatives related to forecasting, reporting standardization, and data governance.

Data Analyst, Finance

• serve as the day-to-day analytics lead for QSR client
• operationalize a measurement ecosystem connecting media investments to consumer behavior and business outcomes
• execute measurement strategies supporting planning, optimization, and business growth
• oversee advanced measurement initiatives including marketing mix modeling, incrementality testing, attribution, brand lift, and consumer research
• influence internal teams and stakeholders through data driven storytelling

Associate Director, Data Analytics

• Providing day-to-day support of the PLM tool and product community, ensure consistency of material master data fields in PLM with other business management systems, validate product data, BOMs, Operations and Financial Planning requirements, collaborate with PLM vendor support team and monitor and review system performance.
• Ensure the Propel PLM system is seamlessly integrated into our operations, supporting product, engineering, manufacturing, and supply chain processes.
• Maintain the PLM system's performance, security, and reliability as the system of record for all products.
• Ensure the accuracy, consistency, and security of PLM data across all platforms.
• Develop and implement data management practices to improve data quality and accessibility.
• Tailor the PLM system to meet operational needs, implementing workflows, user roles, and data structures that support our rapidly evolving manufacturing and engineering processes.
• Work closely with the Operations, Engineering, Business Technology and Product teams to ensure the PLM system enhances our operational capabilities and supports cross-functional initiatives.
• Equip operational teams with the necessary training and support to utilize the PLM system fully, enhancing user adoption and system utility.
• Drive continuous improvement by analyzing system usage, gathering feedback from operational teams, and implementing enhancements to support evolving business needs.
• Lead PLM-related projects within the Operations team, managing timelines, resources, and deliverables to achieve project objectives.
• Champion, role model, and embed Samsara’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices.

PLM Data Analyst

• Ensures data is accurate, complete, and fit for performing data analyses through various testing procedures and data controls
• Develops and executes on Enterprise Data Management policies and standards
• Manages data related incidents and identifies, communicates, and resolves or escalates issues
• Develops, manages, and executes on controls, ensuring tracking, monitoring, and resolution of any control breaches
• Partners with Business and Technology functions

Data Analyst jobs in New York

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Senior AI Data Analyst – Sales

Staff Product Manager, Data & Analytics

Senior Data Analyst

Database Analyst – Clinical Data Collection Strategies

Senior Associate, Data Scientist – Commercial Bank Strategy & Analytics

Client Quantitative Analyst I

Data Analyst

Collision Data Analyst

Real World Evidence Research Analytics Analyst

Business Manager – Marketing, Analytics, Product Strategy

Financial Data Analyst

Technical Product and Data Business Analyst, GCP Analytics

Senior Analyst, Data, Analytics and Machine Learning

Data Analytics Co-Op

Associate Director, Data Strategy & Analytics

Credit Model Development Quantitative Analyst I – HELOC, Residential Mortgage

Data Analyst, Finance

Associate Director, Data Analytics

PLM Data Analyst

Senior Data Analyst