VP, Model Monitoring (L12)

Synchrony

1d•Hybrid

About The Position

Role Title: VP, Model Monitoring (L12) Company Overview: Synchrony (NYSE: SYF) is a premier consumer financial services company delivering one of the industry’s most complete digitally enabled product suites. Our experience, expertise and scale encompass a broad spectrum of industries including digital, health and wellness, retail, telecommunications, home, auto, outdoors, pet and more. We have recently been ranked #2 among India’s Best Companies to Work for by Great Place to Work. We were among the Top 50 India’s Best Workplaces in Building a Culture of Innovation by All by GPTW and Top 25 among Best Workplaces in BFSI by GPTW. We have also been recognized by Ambition Box Employee Choice Awards among the Top 20 Mid-Sized Companies, ranked #3 among Top Rated Companies for Women, and Top-Rated Financial Services Companies. We provide best-in-class employee benefits and programs that cater to work-life integration and overall well-being. We provide career advancement and upskilling opportunities, focusing on Advancing Diverse Talent to take up leadership roles. Organizational Overview: Our Analytics organization comprises of data analysts who focus on enabling strategies to enhance customer and partner experience and optimize business performance through data management and development of full stack descriptive to prescriptive analytics solutions using cutting edge technologies thereby enabling business growth Role Summary/Purpose: The VP, Model Monitoring is a role (Including People Management) within India Analytics Hub (IAH), operating under the Decision Management, reporting to the Model Monitoring Lead in US, is a key stakeholder in the ongoing risk oversight of deployed customer and non-customer facing models across the organization. This role serves as a subject matter expert in model monitoring best practices and governance standards, ensuring early identification of model risk through data-driven diagnostics and analyses. Leveraging advanced analytics, visualization tools, and regulatory understanding, this role ensures models remain robust, interpretable, and aligned with evolving business and regulatory expectations—ultimately safeguarding the integrity of the firm’s model risk management lifecycle.

Requirements

8+ years of of experience model analytics, monitoring, validation, or credit risk strategy within a financial or regulated setting.
Strong technical proficiency in Python, SQL, and data visualization tools like Tableau or Power BI.
Solid understanding of model performance metrics such as KS, AUC, PSI, and statistical indicators of stability and drift.
Ability to synthesize complex technical findings into business-friendly communications and recommendations.
Experience managing multiple projects or monitoring streams, with attention to timelines, quality, and stakeholder expectations.
Experience with data visualization tools like Tableau, Power BI, or similar platforms to create actionable performance dashboards.
Working knowledge of performance drift metrics, stability indicators, and key model health metrics.
Demonstrated ability to synthesize technical insights into business-aligned narratives and actionable recommendations.
Proven project management capabilities with experience leading multiple monitoring initiatives in parallel.
Broad understanding of credit risk, fraud, marketing analytics, regulatory modeling, or consumer lending.
8 to 12 years of experience with Bachelor’s degree in a quantitative, technical, or data-focused field (e.g., Statistics, Mathematics, Computer Science, Data Science, Engineering) with 8+ years’ experience OR, in lieu of degree, and 10 to 12 years relevant work experience in model analytics, monitoring and validation.

Nice To Haves

Exceptional verbal and written communication skills demonstrated through executive and cross-functional stakeholder engagement, detailed-oriented documentation, and visual storytelling.
Advanced critical thinking skills in analytical problem-solving and the ability to use data to break down complex models.
Strong project management and leadership skills to achieve specific goals within a defined timeline and budget.
Familiarity with modern machine learning models, explainability techniques (e.g., SHAP, LIME), and MLOps frameworks.
Ability to effectively share knowledge by translating complex, technical subject matter and providing actionable coaching and feedback across all levels.
Strong business acumen and familiarity with model governance frameworks, regulatory expectations, and internal audit processes (e.g., SR 11-7 compliance, MRM policies).
Technical experience with exploratory data analysis, statistical modeling, machine learning, and generative AI.

Responsibilities

Support the development and execution of the model monitoring roadmap, ensuring the practices are forward-looking, risk-informed, and aligned with business priorities and regulatory expectations.
Lead performance oversight for high-impact models, prioritizing monitoring efforts based on risk, materiality, and business impact—ensuring the right models receive the right level of scrutiny.
Build, mentor, and manage a high-performing analytics team, fostering a culture of innovation, accountability, and continuous learning.
Drive complex performance investigations, including monitoring, reporting, and flagging performance issues to support identification of root causes and business implications and guide coordinated corrective actions
Oversee the design and evolution of monitoring tools, dashboards, and alerting systems that deliver timely, actionable insights to stakeholders and support informed decision-making
Maintain enterprise-wide monitoring standards, defining performance thresholds, stability indicators, and explainability requirements that reflect both regulatory guidance and internal risk appetite.
Champion automation and scalability, leveraging technology and analytics to streamline recurring monitoring routines and ensure consistency, accuracy, and long-term efficiency.
Act as a trusted advisor during audits and regulatory reviews, clearly articulating monitoring outcomes, risk mitigations, and the strength of the monitoring framework.
Collaborate cross-functionally with model developers, users, validators, and risk officers to ensure that performance insights are integrated throughout the model lifecycle—from design to retirement.
Continuously evolve the monitoring function, staying ahead of industry best practices, emerging risks, and new technologies to ensure our capabilities remain strong, relevant, and resilient.
Perform other duties/special projects as assigned