Dun & Bradstreet

Events

• Support the development and execution of D&B’s enterprise-wide event strategy to advance business objectives, elevate brand perception, and deepen client engagement.
• Contribute to high impact experiential programs, including immersive brand activations, integrated event marketing, standout customer experiences, team member moments, and strategic sponsorships aligned to commercial priorities.
• Partner closely with the Director of Events & Experiences to help drive operational excellence, consistently raise the bar on experience design, and deliver high quality events across regions.
• Collaborate cross functionally with marketing peers, business leaders, and other stakeholders to translate business priorities into thoughtful, well executed experiential and sponsorship programs with measurable results.
• Help concept, refine, and execute innovative event programs that strengthen relationships with clients and partners and contribute to commercial growth initiatives.
• Manage end to end event operations, including budget tracking, vendor coordination, sourcing, logistics, risk mitigation, and compliance with internal standards and policies.
• Support the execution of both proprietary and third party events and sponsorships across D&B’s portfolio, including Agenda and content development, Production and vendor management, Contract and financial coordination, Communication with attending teams to ensure preparedness, and Post-event reporting and measurement.

Events & Experiences Manager

Analyst

• Work across range of Analytical Solutions that includes Implementation, Testing, Validation, Documentation, Monitoring, and Reporting.
• Extracting large data from various data sources using multiple tools such as Python/ Pyspark /Hadoop/ SQL/ etc., to perform multiple analysis.
• Architect and create Agentic solutions to achieve operational efficiency.
• Creating data pipelines, performing model scoring, and validating model results. Utilize custom built automated frameworks for all deliverables.
• Work on MLOps/LLMOps frameworks to deploy, monitor and validate AI/ML models.

Analyst II

• Work across range of Analytical Solutions that includes Implementation, Testing, Validation, Documentation, Monitoring, and Reporting.
• Extracting large data from various data sources using multiple tools such as Python/ Pyspark /Hadoop/ SQL/ etc., to perform multiple analysis.
• Creating data pipelines, performing model scoring, and validating model results. Utilize custom built automated frameworks for all deliverables.
• Work with GenAI Frameworks/Tools such as Microsoft CoPilot Studio, LangGraph, etc. to create agentic solutions.
• Work with multiple teams such as Data Supply, ML Engineers, Technology to implement ML/GenAI solutions and models.

Data Scientist

• Build agentic workflows using LangChain/LangGraph and similar frameworks
• Develop autonomous agents for data validation, reporting, document processing, and domain workflows
• Deploy scalable, resilient agent pipelines with monitoring and evaluation
• Develop GenAI applications using models like GPT, Gemini, and LLaMA
• Implement RAG, vector search, prompt orchestration, and model evaluation
• Partner with data scientists to productionize POCs
• Build distributed data pipelines (Python, PySpark)
• Develop APIs, SDKs, and integration layers for AI-powered applications
• Optimize systems for performance and scalability across cloud/hybrid environments
• Contribute to CI/CD workflows for AI models—deployment, testing, monitoring
• Implement governance, guardrails, and reusable GenAI frameworks
• Work with analytics, product, and engineering teams to define and deliver AI solutions
• Participate in architecture reviews and iterative development cycles
• Support knowledge sharing and internal GenAI capability building

Financial Planning and Analysis

• Role focused on Workday Financials, particularly covering configuration, integration, and reporting.
• Foundational Data Model (FDM) Maintenance: Maintain and update Workday’s Foundational Data Model – the multi-dimensional chart of accounts (work tags) framework that underpins all financial transactions and reporting.
• Workday Financials Configuration: Configure and support the Procurement, Accounts Payable (AP), Accounts Receivables (AR), Banking, General Ledger (GL), Assets and Workday Projects modules in Workday Financial Management.
• Integration Development (Workday Studio): Design, develop, test, and deploy integrations between Workday and other internal or third-party systems using Workday Studio.
• Reporting and Analytics Support: Develop and maintain custom reports and dashboards for all Workday financial modules using Workday’s reporting tools.
• Compliance and Best Practices: Ensure Workday configurations and integrations adhere to internal controls, data security policies, and compliance requirements.
• Continuous Improvement: Stay up-to-date with Workday’s semi-annual release updates, especially new features related to Financial Management and Integration.
• Documentation and Training: Create and maintain detailed documentation for configurations, integration designs, workflows, and any custom solutions implemented.

Senior Workday Finance Specialist

• Build agentic workflows using Lang Chain/Lang Graph and similar frameworks
• Develop autonomous agents for data validation, reporting, document processing, and domain workflows
• Deploy scalable, resilient agent pipelines with monitoring and evaluation
• Develop GenAI applications using models like GPT, Gemini, and LLaMA
• Implement RAG, vector search, prompt orchestration, and model evaluation
• Partner with data scientists to productionize POCs
• Build distributed data pipelines (Python, PySpark)
• Develop APIs, SDKs, and integration layers for AI-powered applications
• Optimize systems for performance and scalability across cloud/hybrid environments
• Contribute to CI/CD workflows for AI models—deployment, testing, monitoring
• Implement governance, guardrails, and reusable GenAI frameworks
• Work with analytics, product, and engineering teams to define and deliver AI solutions
• Participate in architecture reviews and iterative development cycles
• Support knowledge sharing and internal GenAI capability building

Senior Analyst

• Develop AI Agents: Design, code, and implement AI agents and copilots using Google's Gemini API and Microsoft Copilot Studio.
• Integrate Systems: Write robust Python code to connect AI agents with enterprise data sources, internal tools, and third-party services via REST APIs.
• Implement RAG Patterns: Build and refine Retrieval-Augmented Generation (RAG) pipelines to ensure agents provide accurate, context-aware responses grounded in proprietary data.
• Prompt Engineering: Craft, test, and iterate on effective prompts to guide agent behavior, ensuring reliability, safety, and desired outcomes.
• Full Lifecycle Development: Participate in the entire development lifecycle, from initial concept and design through to testing, deployment, and maintenance.
• Collaboration: Work closely with senior engineers to overcome technical challenges and with product managers to translate business requirements into functional agent capabilities.
• Troubleshooting: Debug and resolve issues in agent performance, whether they stem from the underlying LLM, the data pipeline, or the integration code.
• Work with analytics, product, and engineering teams to define and deliver AI solutions.
• Participate in architecture reviews and iterative development cycles.
• Support knowledge sharing and internal GenAI capability building.

Data Science Analyst II

AI Engineer

• Build agentic workflows using LangChain/LangGraph and similar frameworks.
• Develop autonomous agents for data validation, reporting, document processing, and domain workflows.
• Deploy scalable, resilient agent pipelines with monitoring and evaluation.
• Develop GenAI applications using models like GPT, Gemini, and LLaMA.
• Implement RAG, vector search, prompt orchestration, and model evaluation.
• Partner with data scientists to productionize POCs.
• Build distributed data pipelines (Python, PySpark).
• Develop APIs, SDKs, and integration layers for AI-powered applications.
• Optimize systems for performance and scalability across cloud/hybrid environments.
• Contribute to CI/CD workflows for AI models—deployment, testing, monitoring.
• Implement governance, guardrails, and reusable GenAI frameworks.
• Work with analytics, product, and engineering teams to define and deliver AI solutions.
• Participate in architecture reviews and iterative development cycles.
• Support knowledge sharing and internal GenAI capability building.

Senior Gen AI Engineer

Analyst II – Data Science

Full-stack Engineer

• Liaise between business stakeholders and technology teams in developing user stories
• Identify system impacts and recommended solutions that meet customer needs
• Maintain Confluence, Jira with key business decisions and technical documentation
• Ensure user stories reflect true requirements and convey business impact to all teams
• Create techno-functional user stories to gain business approval
• Work closely with the business, testers and developers to clarify requirements
• Manage documentation, scope, schedules, and stakeholder relationships for multiple projects

Software Engineer II

Account Executive

• Shape the Future with Dun & Bradstreet
• The Public Sector Job Family is responsible for selling the Company’s products and services to existing clients and developing or expanding business within the Local and Federal Governments that are of significant strategic importance to the Company and will have a major impact on the Company’s long-term success.
• Maintain and grow the revenue stream through renewal management, win-back, cross-sell, up-sell of new opportunities.
• Identify new contacts and deepen relationships with current contacts.
• Generate new business through new client identification.

Account Executive II, SLED

• Maintain and grow the revenue stream through renewal management, win-back, cross-sell, up-sell of new opportunities.
• Identify new contacts and deepen relationships with current contacts.
• Generate new business through new client identification.
• Build and maintain ongoing strategic Executive level customer relationships across the Agency’s/Departments.
• Lead account planning activities with team leader and other sales support team members through quarterly detailed account planning process.
• Meet and exceed overall sales target through the retention and growth of assigned accounts.
• Measure and communicate progress against monthly targets by accurately and timely reporting/forecasting.
• Maintain consistent and accurate data in SFDC to support territory, account planning and forecasting.

Account Executive II

• Ensure the quality, availability, and governance of enterprise data, which is necessary for operational excellence and long-term scalability.
• Develop and implement roadmaps and initiatives through cross-functional partnerships to improve, expand and grow critical data element data quality.
• Understand how critical data elements are processed globally and set data quality standards and guidance for data operations teams. Work with data quality and data supply chain teams to monitor and measure the data against these standards.
• Proactively review data quality results, issues and observations on a regular basis to ensure data quality is maintained and improved. Provide guidance and support to regional teams.
• Develop and publish directives on how data should be managed throughout its lifecycle.
• Understand client insights, usage behaviors and requirements for their assigned CDE/Domain.
• Support client-facing teams in understanding critical data elements and engage product teams to identify business needs and develop, implement, and manage the data asset. Establish and maintain strong relationships with key business and technology stakeholders.
• Serve as a role model, inspiring innovation and teamwork within the team and across departments.
• Continually evaluate processes for improvement, taking the lead in developing and executing plans. Develop innovative alternatives and modern approaches to enhance the areas of our business under our control.
• Stay updated with the latest trends and technologies in data & analytics and apply them to improve existing processes.

Data Manager

Operations

• Utilize an analytical mindset to collect, organize, and deliver large datasets from multiple channels and sources
• Engage in various analytical tasks, including design, development, validation, calibration, documentation, implementation, monitoring and reporting
• Review and validate data to ensure it meets high standards of quality, accuracy, and reliability
• Support continuous improvements in data collection and delivery processes
• Contribute to the creation of tools for monitoring and reporting
• Proactively analyze and troubleshoot data-related issues, assess their criticality, escalate for timely resolution, and participate in problem-solving
• Collaborate with internal and external stakeholders on data compilation, analysis, and quality assurance
• Provide analysis and drive modern solutions and efficiencies in our processes

Data Operations Analyst

Incident Response Analyst

• Lead high‑fidelity alert investigations, performing deep technical analysis to rapidly identify, contain, and remediate threats.
• Own complex incident investigations, driving technically precise conclusions and elevating the organization’s detection and response maturity.
• Champion process development, identifying gaps, designing scalable workflows, and implementing improvements that strengthen the Incident Response program.
• Create and refine technical playbooks, documentation, and response guides, ensuring clarity, consistency, and operational excellence.
• Mentor and uplift junior analysts, providing guidance, coaching, and training to build a high-performing team.
• Serve as the escalation point for critical and ambiguous cases, applying advanced threat analysis and sound judgment under pressure.
• Collaborate with engineering, IT, Legal, HR, and business partners to resolve incidents holistically and drive enterprise-wide security improvements.
• Apply strong analytical and technical expertise to continuously enhance SOC processes, workflows, and response capabilities.
• Contribute to the evolution of our detection landscape, partnering with detection engineering to improve log ingestion, alert logic, and signal quality.
• Assess and mitigate AI‑related security risks, including model misuse, prompt injection, data leakage, and emerging automation attack vectors.
• Participate in an on‑call rotation, serving as a trusted responder for high‑severity incidents.