Vice President, Data Science

S&P Global

Base: $270,600 to $353,063; bonus: annual incentiv...
Not specified (assumed hybrid or fully remote based on industry norms).
20+ years analytics data science ml production experience
Banking capital markets regulated environment expertise
Full model lifecycle ownership from development to monitoring
S&P Global is seeking a Vice President of Data Science to lead the development and operationalization of machine learning models within a regulated financial services environment. The role requires extensive experience in applied data science and machine learning, alongside strong analytical and leadership skills to drive the AI/ML strategy

Job Summary

  • The role exists to ensure AI/ML strategy is sound and that analytical models are correct, explainable, reliable in production, and able to withstand operational and regulatory scrutiny.
  • You will work closely with engineering, data platform, and product teams to take models from problem definition through to production operation, including feature engineering, back-testing, deployment, monitoring, and ongoing performance management.
  • S&P Global offers competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.

Matching Summary

Match Score: 85

S&P Global is seeking a Vice President of Data Science to lead the development and operationalization of machine learning models within a regulated financial services environment. The role requires extensive experience in applied data science and machine learning, alongside strong analytical and leadership skills to drive the AI/ML strategy.

Salary

Base: $270,600 to $353,063; Bonus: Annual incentive plan eligible; Benefits: Health care, flexible downtime, continuous learning, retirement planning

Skills & Requirements

Must-have

  • 20+ years analytics data science ML production experience
  • Banking capital markets regulated environment expertise
  • Full model lifecycle ownership from development to monitoring
  • Time-series analysis predictive modelling statistical grounding
  • Production ML system design batch real-time inference
  • Explainable models feature attribution regulatory scrutiny

Nice-to-have

  • Hands-on technical contribution and code review skills
  • Mentoring other data scientists through pairing
  • Pragmatic outcome-driven mindset with clear communication
  • Experience with complex imperfect datasets and regime changes

Key Requirements

  • 20+ years working with analytics data science or ML systems
  • Significant experience in financial services or regulated domains
  • US candidates only for salary eligibility

Work Rights

Not specified

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