Applied AI ML Lead – Senior Data Scientist

Overview

In this role you will apply advanced data science to shape trustworthy AI solutions for risk and compliance in a leading financial institution. You will collaborate across product, engineering, and business partners to deliver scalable tools that create real business value and support responsible growth. You will experiment and innovate within a diverse team, contributing to strategic AI initiatives that transform processes and client services. This is a mission-driven opportunity to influence risk management at scale and advance your career in a dynamic environment.

Pay / Benefits

• equal opportunity employer
• diversity and inclusion value
• reasonable accommodations for religious practices and disabilities
• career growth opportunities
• inclusive culture
• competitive environment

Responsibilities

• Lead end-to-end model development lifecycle with a focus on scalability and business alignment
• Design and implement multi-agent systems with orchestration layers and human-in-the-loop controls
• Implement drift monitoring and model retraining to sustain accuracy
• Create evaluation frameworks for AI/agentic systems covering prompt quality, agent performance, and business outcomes
• Partner with senior leaders to embed AI into workflows for improved efficiency
• Build and deploy AI and data-driven applications using cloud, data mesh, and knowledge base tech
• Integrate analytics models into operational workflows to drive business value and adoption
• Communicate analytical findings and recommendations to senior leadership

Key requirements

• Experience in data science, analytics or related field
• Proven track record deploying and managing AI/ML models in large-scale enterprise
• Experience with AI/ML algorithms, statistical modeling, and scalable data pipelines
• Experience with A/B experimentation and production-quality code
• Strong communication skills for technical and non-technical audiences
• Scientific mindset with ability to work independently and in teams
• Ability to thrive in a matrix environment and build cross-location partnerships
• Proven experience building and deploying multi-agent systems, including orchestration frameworks and production-grade integration

• Strong written and verbal communication
• Collaborative mindset
• Innovative and independent work style
• AI/ML algorithms
• Statistical modeling
• Scalable data processing pipelines

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