[Hiring] AVP, Model Ops Engineer @Synchrony

Role Description

The AVP, Model Ops Engineer is a role (Individual Contributor) within the India Analytics Hub (IAH), operating under the Decision Management vertical and is responsible for designing and building the data infrastructure, pipelines, and tooling required to support robust, scalable, and automated post-deployment monitoring of models. This role supports model performance tracking, alerting, back testing, and audit readiness by integrating data from across the model lifecycle. The engineer collaborates closely with model developers, product managers, risk partners, and compliance teams to operationalize monitoring strategies aligned with model governance policies. The position is remote, where you have the option to work from home.

Key Responsibilities

• Design, develop, and maintain robust pipelines to collect, transform, and store data used in model monitoring workflows (e.g., scoring data, performance metrics, outcomes).
• Build scalable data architectures to support real-time and batch monitoring, including data ingestion, enrichment, and retention practices.
• Develop reusable monitoring components (e.g., performance drift detectors, threshold-based alerts, metric repositories) that support various model types and regulatory needs.
• Integrate data pipelines with model lifecycle platforms, MLOps tools, and observability solutions to ensure seamless model performance tracking.
• Partner with model risk and compliance teams to ensure data lineage, audit trails, and documentation are preserved and accessible for regulatory reviews (e.g., SR 11-7 compliance).
• Collaborate with data scientists, model validators, and product managers to align monitoring data infrastructure with evolving model monitoring requirements.
• Work closely with the model monitoring analytics and strategy monitoring analytics teams within MO&A to ensure the monitoring data infrastructure adapts to changing analytics and monitoring needs.
• Enable visualization and reporting capabilities through dashboards (e.g., Power BI, Tableau) that summarize model health, stability, and issue alerts.
• Design and maintain high-performance data pipelines that ingest, transform, and version datasets for Model and Strategy Monitoring.
• Optimize data storage and compute performance for large-scale monitoring use cases involving high-frequency scoring or model ensembles.

Qualifications

• Bachelor’s degree in a quantitative, technical, or data-focused field (e.g., Statistics, Mathematics, Computer Science, Data Science, Engineering) with 4+ years’ experience OR, in lieu of degree, and 7+ years of relevant work experience in data engineering.
• 4+ years of experience in MLOps, data engineering or related roles in the financial services or regulated analytics domain.
• Strong proficiency with data engineering tools and frameworks (e.g., Apache Spark, Airflow, Kafka, dbt, PySpark).
• Proficient in programming languages such as SAS, Python, and SQL for building monitoring pipelines and validation checks.
• Experience with cloud-based data infrastructure (e.g., AWS, Azure, GCP) and data warehousing (e.g., Snowflake, Redshift, BigQuery).
• Familiarity with MLOps practices, model metadata tracking (e.g., MLflow), and monitoring toolkits (e.g., Evidently AI, WhyLabs, Prometheus).
• Understanding of model risk governance requirements and the role of data engineering in ensuring compliant model monitoring.
• Ability to work in an agile environment and deliver high-quality, production-grade code in collaboration with DevOps and platform engineering teams.

Desired Skills/Knowledge

• Strong problem-solving skills and experience automating repetitive data monitoring tasks.
• Attention to detail and commitment to maintaining high standards of data quality, integrity, and compliance.
• Experience building alerting mechanisms and diagnostic logging for monitoring model behaviors.
• Excellent communication skills, with the ability to explain complex technical concepts to non-technical audiences and collaborate across teams.
• Exposure to explainability frameworks and the role of data in enhancing model transparency and interpretability.

Work Timing

2:00 PM to 11:00 PM IST. This role qualifies for Enhanced Flexibility offered in Synchrony India and will require the incumbent to be available between 06:00 AM Eastern Time – 11:30 AM Eastern Time (timings are anchored to US Eastern hours and will adjust twice a year locally). This window is for meetings with India and US teams. The remaining hours will be flexible for the employee to choose. Exceptions may apply periodically due to business needs.

Internal Applicants

• Understand the criteria or mandatory skills required for the role, before applying.
• Inform your manager and HRM before applying for any role on Workday.
• Ensure that your professional profile is updated (fields such as education, prior experience, other skills) and it is mandatory to upload your updated resume (Word or PDF format).
• Must not be any corrective action plan (Formal/Final Formal LPP).
• L8+ Employees who have completed 18 months in the organization and 12 months in their current role and level are only eligible.
• Employees at L8+ can only apply for this opportunity.

Grade/Level

10

Job Family Group

Data Analytics