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Skills
Analysis Skillsunmatched
Artificial Intelligence (AI)unmatched
Banking Servicesunmatched
Communication Skillsunmatched
Computer Scienceunmatched
Continuous Improvementunmatched
Cross-Functionalunmatched
Data Modelingunmatched
Data Scienceunmatched
Documentationunmatched
Financial Mathematicsunmatched
Financial Modelingunmatched
Leadershipunmatched
Machine Toolunmatched
Mathematicsunmatched
Mentoringunmatched
Model Reviewunmatched
Natural Language Processing (NLP)unmatched
Performance Analysisunmatched
Performance Tuning/Optimizationunmatched
Predictive Modelingunmatched
Presentation/Verbal Skillsunmatched
Product Lifecycleunmatched
Python Programming/Scripting Languageunmatched
Regulationsunmatched
Regulatory Complianceunmatched
Riskunmatched
Risk Management Framework (RMF)unmatched
Risk Modelingunmatched
Statisticsunmatched
Team Lead/Managerunmatched
Technical Leadershipunmatched
Technical Operationsunmatched
Technical Presentationunmatched
Technical Strategyunmatched
Description
Position: SENIOR MODELING LEAD YEARS OF EXPERIENCE: 9-10+ YEARS Location: Plano, TX & San Antonio, TX Salary range: $145k-$165K+12% Incentive & Benefits. Position Overview We are seeking a Senior Modeling Lead to provide strategic and technical oversight across multiple AI/ML workstreams. In this role, you will direct a team of data scientists / modelers through full model development lifecycle, ensure consistency in modeling standards and governance practices, and serve as primary liaison between technical teams and senior stakeholders. Ideal candidate brings 9-10+ years of modeling experience and a proven ability to operate effectively at both strategic and technical levels.
Relevant Team Lead experience (at least 3 years)in Banking domain
Hands on experience in Model Development, Model Monitoring of advanced ML/quantitative/finance models
Strong proficiency in Python; familiarity with modern AI/ML frameworks, ML-Ops, and large-scale data platforms.
Key Responsibilities
Provide strategic and technical leadership across multiple AI/ML modeling workstreams, ensuring alignment with business
Oversee full model lifecycle across all workstreams — including development, validation, independent assessment, performance optimization, monitoring, documentation, and governance.
Establish and enforce consistent modeling standards, methodology frameworks, explainability practices, and bias testing protocols across team.
Act as a primary escalation point for model risk, governance issues, technical challenges, partnering with risk, compliance as needed.
Lead model review and approval processes, ensuring all models meet internal governance requirements and applicable regulatory standards.
Translate complex modeling outcomes and technical findings into clear, actionable insights for executive and non-technical stakeholders.
Drive evaluation and adoption of emerging AI/ML tools, platforms, and methodologies, providing evidence-based recommendations to leadership.
Recruit, mentor, and develop a high-performing team of senior and mid-level modelers, fostering a culture of technical rigor and continuous improvement.
Define team's long-term analytical roadmap, balancing innovation with BAU delivery.
Collaborate cross-functionally with data engineering, technology, operations, and business teams to align modeling solutions with broader organizational objectives.
Qualifications & Experience
10+ years of progressive experience in quantitative modeling, data science, or applied AI/ML, with at least 3 years in a team leadership or senior technical lead capacity.
Broad expertise across multiple modeling domains, such as predictive analytics, NLP, optimization, or AI platform evaluation.
Strong proficiency in Python; familiarity with modern AI/ML frameworks, MLOps tooling, and large-scale data platforms.
Deep understanding of end-to-end model lifecycle, including model risk management, validation frameworks, and regulatory expectations.
Proven ability to lead and develop cross-functional modeling teams in a fast-paced, delivery-oriented environment.
Experience engaging with model risk, audit, compliance, or regulatory stakeholders, and navigating governance and approval processes.
Exceptional communication skills & ability to present complex technical concepts clearly to stakeholders.
Track record of driving adoption of emerging AI/ML technologies in a structured manner.
Advanced degree (Master’s or PhD) in Statistics, Computer Science, Mathematics, Data Science, or a related quantitative discipline preferred.