Key Responsibilities
As the Data Science Team Lead for Risk, you will be responsible for:
Technological and Strategic Leadership: Defining and implementing the Data Science strategy for the Risk domain, while identifying critical business and technological opportunities.
Hands-on Development: Actively working on the development, building, and deployment of critical Machine Learning and Gen-AI models for identifying, classifying, and preventing risks and fraud.
Team Management and Mentoring: Managing and guiding a team of talented Data Scientists, including work planning, professional development, providing mentorship, and contributing to talent acquisition.
AI Agents Innovation: Leading the team's efforts in the field of AI Agents within Risk, including architectural design, developing complex Agent Workflows, advanced Prompt Engineering, and developing rigorous Evaluation methodologies to ensure reliability and accuracy in production.
Cross-Functional Collaboration: Managing strategic relationships and collaborations with Engineering, Product Managers, Analysts, and other stakeholders to ensure solutions meet critical business needs.
Production Deployment: Ensuring Data Science solutions transition reliably, scalably, and efficiently from concept to production and making significant impact.
5+ years of experience as a Data Scientist, with at least 2 years of proven experience in managing or leading a team of data scientists.
Strong background and practical experience developing and leading end-to-end Machine Learning projects.
Experience working closely with development teams
Proven hands-on experience working with Large Language Models (LLMs), including:
Building Agent-Based Frameworks to solve complex problems.
Advanced Prompt Engineering.
Defining and building Agent Workflows that interact with data sources and APIs.
Establishing and executing comprehensive validation frameworks of Gen-AI solutions.
Excellent interpersonal and leadership skills: ability to manage and develop people and build strong relationships with key internal partners.
Ability to take full ownership of projects, from initial idea through to deployment in production.
Experience working in a Big Data environment and at scale.
B.Sc in Computer Science, Physics, Mathematics, Electrical Engineering, Statistics, or a related quantitative field
