Global Head – Data Science
S&P Global
full-time
Posted on:
Location Type: Hybrid
Location: New York City • New Jersey • New York • United States
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Salary
💰 $177,036 - $300,000 per year
Job Level
About the role
- Lead the design, development, and operation of high-rigor analytical and machine-learning systems across a complex, regulated financial-services estate.
- Define the AI/ML roadmap for Enterprise Solutions while building analytical and predictive models.
- Ensure AI/ML strategy is sound and analytical models are correct and reliable.
- Collaborate with engineering, data platform, and product teams to take models to production.
- Get involved early in complex or high-risk analytical problems and address issues when models degrade in production.
- Provide hands-on technical contribution, review, and influence.
Requirements
- 20+ 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.
- Clear communicator who can explain modelling choices, assumptions, and limitations to engineers, product partners, and senior stakeholders.
- Acts as a technical mentor to other data scientists through review, pairing, and example, limited people management where appropriate.
Benefits
- 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.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningdata sciencepredictive modelingstatisticstime-series analysisfeature engineeringmodel validationmodel deploymentanomaly detectionexplainable models
Soft Skills
clear communicationtechnical mentorshipcollaborationproblem-solvinganalytical thinkingleadershipinfluencereview and feedbackadaptabilitystakeholder engagement