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Vice President, Data Science

Job in New York, New York County, New York, 10261, USA
Listing for: S&P Global, Inc.
Full Time position Listed on 2026-10-04
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 177036 - 350000 USD Yearly USD 177036.00 350000.00 YEAR

Job Description & How to Apply Below

About the Role

Grade Level (for internal use): 15 The Team:
Enterprise Solutions (ES) Technology is a powerful combination of world class people and businesses with a shared mission and legacy of evolving markets and delivering for the most demanding customers in the world. We are the catalyst to bring data, software, services, and expertise together to power the markets of the future. We drive growth through world class execution, a growth mindset, and our unique expertise and passion for building innovative and connected solutions.

We collaborate with our business line to drive business growth by focusing on execution of our joint product strategies. We ensure that we maximize business value while at the same time minimizing cost of ownership of our technology estate.

Responsibilities and Impact

Define and lead the AI/ML and applied data science roadmap for Enterprise Solutions, shaping high-rigor analytical capabilities across a complex, regulated global financial-services environment. Design, build, and operate production-grade models for anomaly detection, variance analysis, drift detection, forecasting, behavioural signals, and prediction, ensuring they are accurate, explainable, resilient, and regulator-ready. Own the full model lifecycle from problem framing, data exploration, feature engineering, back-testing, validation, deployment, monitoring, tuning, and incident response when models degrade or fail in production.

Partner closely with engineering, data platform, product, and business teams to translate complex analytical problems into scalable, production-ready ML systems that deliver measurable operational and business outcomes. Act as a hands-on technical authority and multiplier, reviewing models, guiding senior practitioners, improving data quality and monitoring standards, and influencing decisions through deep expertise rather than formal authority. Gain high-impact exposure to senior technology leaders, market-facing financial-services platforms, regulated AI/ML practices, and global enterprise-scale transformation, with the opportunity to shape how advanced analytics and machine learning are applied safely and effectively in production.

Compensation/Benefits

Information

S&P Global states that the anticipated base salary range for this position is $177,036 to $350,000. Final base salary for this role will be based on the individual’s geographic location, as well as experience level, skill set, training, licenses and certifications. In addition to base compensation, this role is eligible for an annual incentive plan. This role is eligible to receive additional S&P Global benefits.

For more information on the benefits we provide to our employees, please .

What we are looking for
  • 25+ years of experience in analytics, data science, and machine learning, with a strong track record of delivering and operating production-grade models within financial services or other highly regulated, high-availability environments.
  • Deep expertise in applied data science and ML, including statistical modelling, predictive analytics, model development, validation, deployment, monitoring, and optimisation across the full model lifecycle.
  • Strong hands-on technical skills, with the ability to work directly with data, code, ML frameworks, and complex datasets, while partnering effectively with software engineering and platform teams.
  • Experience building scalable, reliable, and explainable AI/ML solutions that meet operational, governance, and regulatory requirements and deliver measurable business outcomes.
Additional

Preferred Qualifications
  • Pragmatic and outcome-oriented mindset, focused on delivering models that perform reliably in production and create tangible business value.
  • Excellent communication and stakeholder management skills, with the ability to clearly explain modelling decisions, assumptions, risks, and limitations to both technical and non-technical audiences.
  • Influential leadership and collaboration, capable of driving alignment and technical excellence across cross-functional teams without relying on formal authority.
  • Coaching and mentoring capability, guiding and developing data scientists through technical reviews, knowledge sharing, hands-on support, and leading by example.
Right to Work Requirements

This role is limited to persons with indefinite right to work in the United States.

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