S&P Global Market Intelligence
Financial Services
VicePresident,DataScience
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“Vice President, Data Science at S&P Global Market Intelligence. Skills: Data Science Leadership, Machine Learning Engineering, Production ML Systems, Financial Services Analytics. Lead design, development, operation of analytical and ML systems. Define AI/ML roadmap”
What You'll Achieve.
Deliver next-generation, high-scale technology platforms; Enhance digital presence; Improve customer engagement; Production-grade models; Models that run reliably in production; Models that adapt to changing conditions; Models that withstand scrutiny; Drive sustained improvement
Industry & Context.
High-rigor analytical systems; High-rigor predictive models; Anomaly detection; Variance analysis; Drift detection; Forecasting; Prediction; Complex analytical problems; Model degradation or failure; Knowing when to apply advanced modelling; Data quality; Anomaly detection; Monitoring
What They're Looking For.
Must Have
20+ years working with analytics, data science, or ML systems in production, Significant experience in financial services or other regulated, high-availability domains, 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, 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, Understanding of production ML system design, Experience operating models in production over time, Practical experience designing explainable models suitable for regulated environments, Experience combining statistical models, ML, semantic models, and rules-based logic, Focus on data quality, anomaly detection, and monitoring
Nice to Have
PhD preferred, Specific ML framework experience, Cloud platform certs
What You'll Do.
operation of analytical and ML systems
Build analytical and predictive models
Ensure AI/ML strategy is sound
Ensure analytical models are correct
Work with engineering
Take models from problem definition to production
Manage feature engineering
Handle model degradation or failure in production
Apply advanced modelling appropriately
Drive impact through hands-on technical contribution
Focus on data quality
How You'll Work.
Team & Collaboration
Work closely with engineering, data platform, and product teams; Collaborate closely with software engineers and platform teams; 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
Communication Scope
Clear communicator; Explain modelling choices, assumptions, and limitations to engineers, product partners, and senior stakeholders
Full Job Description
# **About the Role:** **Grade Level (for internal use):** 15 **The Team** The Enterprise Solutions Technology team is dedicated to delivering next-generation, high-scale technology platforms through resilient architecture, data excellence, and engineering innovation. Our mission is to enhance our digital presence and improve customer engagement across various domains, including Lending, Corporate Actions, Tax, Regulatory & Compliance, Regulatory Reporting, Public Markets, and Private Markets portfolio monitoring. **Role** We are seeking a Data Scientist Leader to lead the design, development, and operation of high-rigor analytical and machine-learning systems across a complex, regulated financial-services estate. This is a strategy-led and hands-on applied data science and ML engineering role, responsible for defining the AI/ML roadmap for Enterprise Solutions while also building high-rigor analytical and predictive models for anomaly detection, variance analysis, drift detection, market and behavioral signals, forecasting, and prediction. The expectation is production-grade models, comparable in rigor to fraud, risk, or surveillance systems. **Compensation/Benefits Information:** (This section is only applicable to US candidates) S&P Global states that the anticipated base salary range for this position is $2,07060 to $3,53,063. 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 not eligible for additional compensation such as an annual incentive bonus or sales commission plan.This role is eligible to receive additional S&P Global benefits. For more information on the benefits we provide to our employees, please click [here](https://spgbenefits.com/benefit-summaries) **What 's In for you : ** The role exists to ensure AI/ML strategy is sound and that anal
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