AI/ML - Chief Financial Risk Office - Vice President
Salary not listed • Jersey City, NJ, United States • Full-time
Posted 4d ago
No salary is listed. Many US states require employers to post a pay range, so ask about pay early.
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Agent Engineer
About the job
As a Vice President, Data Scientist in the Data Science team within Risk Management and Compliance, you will help shape the future of financial services by developing and implementing advanced AI solutions. You will collaborate with product, engineering, and business partners to create impactful, scalable tools that drive real business value. In this role, you will have the opportunity to experiment, learn, and innovate alongside a diverse team, leveraging your expertise in data science and finance. Together, we will deliver solutions that transform how we operate and serve our clients. Join us to make a meaningful difference and grow your career in a dynamic, inclusive environment.
Responsibilities
- Manage the end-to-end model development lifecycle, ensuring scalability and alignment with business objectives.
- Design and implement multi-agent systems, including orchestration, task routing, and human-in-the-loop controls.
- Implement drift monitoring and model retraining processes to maintain performance.
- Define and implement evaluation frameworks for AI/agentic systems, covering prompt quality, agent performance, and business outcomes.
- Collaborate with senior leaders to re-engineer processes by embedding AI into current workflows.
- Design, build, and deploy AI and data-driven applications using cloud, data mesh, and knowledge base technologies.
- Integrate advanced analytics models and applications into operational workflows.
- Communicate analytical findings and recommendations to senior leadership.
Requirements
- Minimum 6+ years of experience in data science, analytics, or a related field.
- Proven track record of deploying, operationalizing, and managing AI, ML, and advanced analytics models in a large-scale enterprise environment.
- Experience with AI/ML algorithms, statistical modeling, and scalable data processing pipelines.
- Experience with A/B experimentation and developing/debugging production-quality code.
- Strong written and verbal communication skills for technical and business audiences.
- Scientific mindset with the ability to innovate and work independently and collaboratively.
- Ability to thrive in a matrix environment and build partnerships across teams and locations.
- Proven experience building and deploying multi-agent systems, including use of orchestration frameworks (e.g. LangGraph, ADK), agent design patterns, and production-grade system integration.