Vice President, Data Science

S&P Global

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
New York, NY
Salary
$177,036–$350,000 / yr
Posted
31 days ago
Freshness
Confirmed live yesterday
Closes
Jul 22, 2027

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $195k
This role $264k
$117k most similar roles pay here $375k

This role pays more than 82% of similar roles. Most pay $159,093–$231,625 — the shaded band above. At the midpoint, this role pays about $264k versus about $195k for comparable roles.

Based on 240 similar postings.

Employer

About S&P Global

S&P Global delivers Essential Intelligence® that shapes decision making. We provide the world’s leading organizations with the right data, connected technologies and expertise they need to move ahead.

S&P Global currently has 46 open roles on FindRole.

Listed pay typically runs $142,000–$200,000 across 37 roles with salary data.

Most-posted roles

View all roles at S&P Global

At a glance

TL;DR · Vice President, Data Science

Vice President, Data Science joins the Enterprise Solutions team to define and lead the AI/ML and applied data science roadmap within a complex, regulated global financial-services environment. The role involves designing, building, and operating production-grade models for anomaly detection, variance analysis, drift detection, forecasting, behavioral signals, and prediction. You will manage the full model lifecycle, including problem framing, feature engineering, back-testing, validation, deployment, monitoring, and incident response. This position requires deep expertise in statistical modeling, predictive analytics, and machine learning frameworks to create scalable, explainable systems that meet rigorous governance requirements. You will serve as a technical authority, collaborating with engineering and product teams to translate complex analytical problems into production-ready solutions while mentoring senior practitioners and improving data quality standards across the organization to deliver measurable operational outcomes in high-availability environments.

What you'll do

  • Define and lead the AI/ML and applied data science roadmap for Enterprise Solutions.
  • Build and operate production-grade models for anomaly detection, forecasting, and behavior analysis.
  • Manage the full model lifecycle including feature engineering, back-testing, deployment, and incident response.
  • Translate complex analytical problems into scalable, production-ready machine learning systems with business partners.
  • Act as a technical authority by reviewing models and improving data quality standards.
  • Mentor senior practitioners and guide teams through technical reviews and knowledge sharing.
  • Ensure all AI/ML solutions meet strict regulatory requirements and are explainable for financial services.

What we're looking for

  • Must have 25+ years of experience in analytics, data science, and machine learning.
  • Experience must include delivering production-grade models in financial services or highly regulated environments.
  • Expertise is required in the full model lifecycle including development, validation, deployment, monitoring, and optimization.
  • Must possess hands-on technical skills with data, code, ML frameworks, and complex datasets.
  • Ability to build scalable, reliable, and explainable AI/ML solutions that meet governance and regulatory requirements.
  • Strong communication skills to explain modeling decisions and risks to both technical and non-technical audiences.
  • Proven ability to lead, mentor, and influence cross-functional teams without formal authority.
  • Must have an indefinite right to work in the United States.

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