Vice President, Data Science

S&P Global

Data Scientist Leader designing and developing machine learning systems in the financial services sector at S&P Global. Collaborating with engineering teams to deploy analytical models and ensuring compliance with regulations.

Posted 6/26/2026full-timeNew York City • New York, North Carolina • 🇺🇸 United StatesLead💰 $177,036 - $350,000 per yearWebsite

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

25+ years working with analytics, data science, or ML systems in production, with significant experience in financial services or other regulated, high-availability domains.
Strong experience delivering applied data science and machine learning in production within banking, capital markets, or similarly regulated, data-intensive environments.
Deep grounding in statistics, machine learning, time-series analysis, and predictive modelling, with experience building models under real operational constraints.
Hands-on ownership of the full model lifecycle: data exploration, feature engineering, model development, back-testing, validation, deployment, monitoring, and ongoing tuning.
Extensive experience working with large, complex, and imperfect datasets, including missing data, outliers, regime changes, noisy labels, and evolving schemas.
Strong understanding of production ML system design, including batch vs real-time inference, model serving patterns, performance trade-offs, and failure modes.
Experience operating models in production over time, including versioning, drift detection, retraining strategies, and incident response when models misbehave.
Practical experience designing explainable models suitable for regulated environments, including feature attribution and model transparency techniques.
Experience combining statistical models, ML, semantic models, and rules-based logic where needed to achieve accuracy, stability, and explainability.
Strong focus on data quality, anomaly detection, and monitoring, including metrics that surface real issues and drive sustained improvement.

Benefits

Comp & perks

Health & Wellness: Health care coverage designed for the mind and body.
Flexible Downtime: Generous time off helps keep you energized for your time on.
Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.
Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.
Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families.
Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learningdata sciencepredictive modelinganomaly detectionvariance analysistime-series analysisfeature engineeringmodel developmentmodel validationmodel monitoring

Soft Skills

collaborationproblem-solvingownershipcommunicationanalytical thinkingadaptabilityattention to detailcritical thinkingleadershipresponsiveness