Data Science Director

Overview

As a Data Scientist at DTCC, you will lead AI research and prototype development to expand enterprise AI capabilities. You will guide the technical vision and collaborate with product and engineering teams to translate ideas into scalable solutions. Your work will impact strategic initiatives, data governance, and measurable business outcomes. This is an opportunity to shape AI-driven transformation in a leading financial services infrastructure provider.

Pay / Benefits

• competitive compensation
• health and life insurance
• pension
• paid time off
• flexible/hybrid work model
• well-being benefits

Responsibilities

• Define the AI strategy and adopt new technologies like generative AI and LLMs
• Hire, mentor, and lead data scientists to build a high-performing team
• Oversee end-to-end data science projects from concept to deployment (MLOps)
• Partner with Product, Engineering, and Business leaders to align data initiatives with ROI
• Ensure high standards for data modeling, ML algorithms, and methodologies
• Set data collection, quality, and usage standards across the organization
• Define KPIs and track model and data initiative effectiveness

Key requirements

• Minimum 10 years of relevant experience in data science, ML, or applied AI with leadership experience
• Strong expertise in ML/AI techniques, including statistical modeling, generative AI, LLMs, and modern AI frameworks
• Experience researching and prototyping emerging AI technologies, including agent-based systems, prompt orchestration, and advanced experimentation methodologies
• Strong data and analytical skills, including proficiency in SQL and data platforms such as Snowflake or equivalent
• Ability to design and evaluate AI experiments and translate insights into technical recommendations and architectural guidance
• Curiosity and innovative mindset with ability to identify and explore new technologies
• Strong collaboration and communication skills to explain complex AI concepts to diverse stakeholders
• Technical leadership and mentoring experience, contributing to AI research best practices

• collaboration
• communication
• curiosity
• machine learning
• generative AI
• large language models (LLMs)

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