S&P Global

Architect

• The Process Architect is responsible for the proactive development and enhancement of end-to-end processes within the organization.
• This role involves monitoring process performance, prioritizing investments, and driving implementation initiatives.
• Collaborate regularly with stakeholders to identify pain points and uncover new opportunities for process improvement.
• Establish End-to-End Process Vision & Develop Process Roadmap.
• Stay informed about industry trends and leading practices to guide strategic direction and process enhancements.
• Monitor Process Performance & Identify Opportunities.
• Continuously assess end-to-end process performance, providing governance for process adoption and aligning with business demand.
• Evaluate and prioritize opportunities focused on reducing costs, increasing efficiency, and maximizing returns on investment.
• Collaborate with the Center of Excellence (CoE) and Value Consultants to provide insights for business cases.
• Develop process playbooks intended for use in Train the Trainer programs.
• Conduct training sessions for functional users, including Lean Six Sigma Green Belt training.
• Facilitate process design workshops to map current ('as-is') and proposed future ('to-be') workflows.
• Engage with configuration teams to ensure adherence to functional designs and coordinate user testing with business stakeholders, addressing any issues that arise.

Process Architect

Full-stack Engineer

• In partnership with Product, defining and executing the engineering roadmap for SaaS-based enterprise catalog solutions, including integration with bespoke or proprietary internal systems.
• Shepherding the end-to-end software development lifecycle, from requirements gathering and system design through to cloud-native deployment automation.
• Architecting shared capabilities, in a shift-left environment enabling federated consumption across divisions and business units of S&P Global.
• Ensuring systems are secure, compliant, auditable, and observable in-alignment with Enterprise standards.

Associate Director, Software Engineering

Machine Learning Engineer

• Develop Advanced ML Systems: Create, refine, and deploy machine learning systems that solve complex business problems and power Kensho products.
• Build Retrieval-Driven AI Agents: Design AI agents that fetch, validate, and structure data from S&P datasets, ensuring answers produced by LLMs are grounded in S&P’s data universe.
• Evaluate LLM-based Agents: Identify and resolve performance gaps in both online and offline settings, addressing issues such as performance, latency, memory usage, compute efficiency, and feature consistency.
• Work With Domain Specific Data: Leverage proprietary structured and unstructured datasets, deep dive to have domain understanding, work with Subject Matter Experts (SMEs).
• Scale ML Applications: Optimize and scale ML systems to support high demand, efficient resource utilization, and reliable production behavior.
• Reduce Technical Debt: Proactively identify areas of the stack that can be improved, and propose solutions that strengthen reliability and maintainability.
• Taking Initiative: Scope, plan, and execute ML initiatives that develop core capabilities across Kensho products.
• Collaborate Across Teams: Work closely with Data, Product, Design, and Engineering teams to ensure smooth operations and contribute to long-term product vision.
• Improve User Experiences: Partner with Product and Design to develop ML-driven functionality that enhances user workflows and aligns with business needs.
• Drive the ML Lifecycle: Engage in all phases of the ML lifecycle, from problem framing and data exploration to model deployment and production monitoring, ensuring continuous improvement.

Sales

• Drive growth strategy by acquiring net-new business while nurturing high-value relationships with existing clients.
• Act as a trusted advisor engaging directly with C-suite executives, Investor Relations leaders, and Corporate Communications teams.
• Consult on our suite of investor relations analytics, AI, and data solutions to drive workflow efficiency and business intelligence.
• Manage a robust pipeline of new business opportunities through strategic prospecting and targeted outreach.
• Partner closely with Account Management teams to optimize lead generation, identify synergies, and execute comprehensive growth strategies.

Associate Sales Director – Issuer Solutions

Art Director

• Lead the evolution of the ClearPar product portfolio (including Loan Platforms, ADFlow, Loan Processor, Message Director, Document Delivery, and ClearPar Analytics).
• Directly influence how market participants execute critical post-trade and servicing processes—improving speed, transparency, and control across the syndicated loan lifecycle.
• Set product vision and strategy for the ClearPar portfolio, linking near-term roadmaps and delivery to a longer-term platform direction and business outcomes.
• Monitor external market trends (broadly syndicated loans, private credit, post-trade/operations, regulation, and competitive landscape) and translate insights into scenarios, options, and investment recommendations.
• Build, maintain, and communicate a prioritized product roadmap; secure alignment and buy-in from senior leaders and key stakeholders across the enterprise.
• Lead discovery and requirements definition: customer interviews, workflow mapping, user stories, acceptance criteria, and clear product documentation that supports scalable delivery.
• Partner closely with Technology to execute delivery using agile practices (Scrum/Kanban), ensuring timely, high-quality releases and measurable outcomes.
• Define and manage product KPIs (adoption, client outcomes, operational efficiency, quality, revenue enablement), using data to validate decisions and continuously improve.
• Serve as an escalation point for complex client, product, and delivery issues—driving resolution while maintaining quality standards and stakeholder confidence.
• Lead, coach, and develop a globally distributed team: set clear objectives, establish accountability for outcomes, and foster collaboration, continuous improvement, and strong communication.
• Collaborate across business units and geographies to incorporate diverse perspectives and ensure solutions align to broader Enterprise Solutions and S&P Global strategy.

Director, Product Analysis and Design

Project Manager

• Provide day-to-day guidance/coaching to Research Assistants and Rating Analysts.
• Drive consistency/scalability by codifying standard work and promoting disciplined adoption.
• Strengthen AI-enabled productivity by creating reusable assets and proposing lightweight automations.
• Own surveillance/updates for assigned portfolio, synthesizing performance metrics into insights.
• Engage with external parties and craft client stories that translate complex data into narratives.

Senior Analyst – Infrastructure Project Finance Ratings

Backend Engineer

• Solve problems, analyze, and isolate issues
• Build solutions to develop/support key business needs
• Engineer components and common services based on standard development models, languages, and tools
• Produce system design documents
• Collaborate effectively with technical and non-technical partners
• Leading a small team and deliver high value products
• Quickly learn new and internal technologies.

Senior .Net Fullstack Developer

• Lead end-to-end delivery of complex programs and product initiatives, from discovery through launch and post-release optimization
• Develop and maintain a comprehensive project plan with clear objectives, milestones, deliverables, dependencies, and timelines across multiple scrum teams
• Lead the planning and tracking of cross-functional roadmaps in alignment with product and technology strategies
• Establish project governance, status reporting, risk tracking, and issue resolution mechanisms
• Partner with senior stakeholders across Commercial, Finance, Legal, Product, and Technology to ensure alignment and buy-in at all stages of delivery
• Provide transparent, timely updates on program status, risks, and dependencies to leadership and cross-functional teams
• Influence and coordinate with dependent teams to ensure delivery of business-critical components (e.g., user guides, training materials)
• Operate within the SAFe Agile framework, coordinating with RTEs, scrum teams, and solution managers to ensure agile best practices are followed
• Lead the development of a robust change management plan, including establishing KPIs and usage analytics, to support system and process adoption across global teams
• Work with business units to deliver user-focused communication, training, and documentation
• Ensure seamless handoff and integration with ongoing operations and support teams

Project Delivery Manager – Commercial Product Management

General

• Own the operational data picture of the product organization.
• Surface patterns, risks, and opportunities before they become escalations.
• Build and maintain a single operational dashboard.
• Establish a disciplined prioritization framework that evaluates every initiative.
• Continuously refine team practices, tools, and operating rhythms.
• Own the product organization's tool stack and ensure it serves the team.
• Standardize operating rhythms across all four functions.
• Identify and eliminate process friction across the organization.
• Coordinate the release management process across Execution, Data, and UX.
• Serve as the primary operational interface between the product organization and Finance, HR, Technology, and Revenue leadership.

Product Excellence Lead

Data Engineer

• Lead strategic MDM integration initiatives - Architect and oversee seamless, high-volume data integration between Databricks lakehouse and NeoXam MDM platform, establishing foundational data architecture for multi-billion-dollar index-linked investment products
• Drive advanced cloud data architecture - Utilize cutting-edge Databricks features including Unity Catalog, Delta Live Tables, and Serverless compute to optimize data pipelines and maximize performance for massive-scale financial datasets
• Pioneer AI/ML automation solutions - Implement Databricks Mosaic AI and agentic frameworks to automate data transformation, quality assurance, and anomaly detection across the entire conversion lifecycle
• Build and scale high-performing engineering teams - Lead, manage, and grow multiple teams of product-focused software and data engineers while mentoring their professional and technical development
• Modernize legacy infrastructure - Spearhead mission-critical migration of legacy assets and terabytes of data to modern AWS cloud ecosystem, breaking monolithic applications into microservice architectures
• Champion engineering excellence and innovation - Foster a culture of cutting-edge technology adoption, continuous improvement of software engineering practices, and delivery of scalable, resilient solutions

Senior Director, Software Engineering – Data Platform, MDM Integration

Program Manager

• Own and continuously evolve the end-to-end Institute workflow.
• Translate strategy into executable processes, governance rhythms, decision points, and playbooks.
• Build and maintain the operating model infrastructure that enables the Institute to scale from pilot to BAU, while developing integrated delivery calendars and resourcing views that provide clear visibility into capacity, commitments, and enterprise priorities.
• Serve as the day-to-day execution lead between the Institute and key stakeholder groups, including divisions, Editorial, Marketing, Communications, the CEO’s Office/Strategy, CCO, Public Affairs, and other priority enterprise partners.
• Coordinate inputs, sequencing, dependencies, and decision points across divisions to support flagship outputs.
• Ensure contributors have clear expectations on timing, roles, responsibilities, and escalation paths.
• Facilitate alignment forums and working rhythms that keep delivery on track and reinforce enterprise-wide accountability.
• Track progress against editorial calendars, delivery milestones, and enterprise commitments.
• Surface risks, trade-offs, and capacity constraints early, with clear options and recommendations.
• Partner with the Head of the S&P Global Institute on prioritization, sequencing, and resourcing decisions to sustain throughput, quality, and strategic focus as the Institute scales.
• Lead the Institute’s performance reporting and measurement discipline. Track impact, quality, speed, adoption, and stakeholder engagement. Produce dashboards, quarterly readouts, and decision-ready insights for the Head of the Institute, co-sponsors, and steering touchpoints with division and business leaders.

Global Institute Program Manager

Operations

• Own the end-to-end outside counsel lifecycle: panel management, engagement intake, onboarding, performance evaluation, and offboarding.
• Maintain and enforce the Company’s Outside Counsel guidelines, manage billing, and drive cost rigor across external legal spend.
• Lead rate negotiations with outside counsel firms; drive convergence and panel optimization initiatives to consolidate work with preferred providers.
• Lead efforts that push automation, AI, and data-driven insights into how we deliver our work throughout the organization.
• Assist in developing and executing the technology strategy and product roadmap across the LGASRC functions.
• Evaluate, select, and implement new technologies and AI-powered tools to improve operational efficiency and scale service delivery.
• Manage external vendors and consultants to ensure effective partnerships and strong ROI.
• Manage the e-billing platform (configuration, workflows, timekeeper rate approvals, LEDES compliance, and reporting).
• Partner with cross-functional stakeholders to build annual outside counsel budget and forecasts on a regular cadence.
• Produce monthly and quarterly spend reports and executive dashboards for senior stakeholders.
• Identify and implement process improvements, automation, and data quality initiatives across the outside counsel program.
• Benchmark practices against industry peers and lead change management for new policies and tools.

Operations & Technology Senior Manager

Data Scientist

• Lead the design, development, and operation of high-rigor analytical and machine-learning systems across a complex financial-services estate.
• Define the AI/ML roadmap for Enterprise Solutions while also building high-rigor analytical and predictive models for various applications including anomaly detection, variance analysis, and forecasting.
• Collaborate closely with engineering, data platform, and product teams to take models from problem definition through to production operation, including feature engineering and deployment.
• Get involved early in complex or high-risk analytical problems and respond when models degrade or fail in production.
• Apply advanced modeling techniques, knowing when simpler approaches are sufficient.

Vice President, Data Science

Director

• Act as senior reference point coaching (Research Assistants, Rating Analysts and Senior Analysts) on credit fundamentals, modelling discipline, data quality, and standard work including how to use AI as an enabler with governance.
• Coordinate work across credits; anticipate capacity/quality risks; influence outcomes through planning and constructive challenge in ambiguous situations.
• Embed continuous improvement into routines by improving playbooks/SOPs/prompt libraries and driving adoption.
• Partner with stakeholders to identify and shape high-impact use cases, supporting testing/adoption/rollout with governance, controls, and change management.
• Foster a critical thinking mindset challenging assumptions and the status quo to generate insights that shape market views and strategic decisions.

Associate Director – Infrastructure

• Provide day-to-day guidance/coaching to Research Assistants and Rating Analysts, building capability in credit, data discipline, and tooling and reinforcing values-led behaviors.
• Drive consistency/scalability by codifying standard work and promoting disciplined adoption to strengthen trusted, repeatable insights.
• Strengthen AI-enabled productivity by creating reusable assets and proposing lightweight automations that free capacity for human analysis and relationship work.
• Foster continuous improvement by proposing enhancements that remove manual steps without compromising governance or judgement.
• Lead end-to-end execution for assigned credits, ensuring high-quality analysis and timely delivery across priorities with clear accountability.