Executive Director, Data Science

The Executive Director Data Scientist will lead our data team within the Applied AI & Analytics Solutions product group, driving innovation in AI, machine learning, and advanced analytics. This role is pivotal in exploring, piloting, and implementing cutting-edge data-driven solutions that address complex business challenges. The ED Data Scientist will spearhead research and development efforts and nurture a culture of experimentation and innovation, ensuring seamless integration of solutions into operational workflows and collaboration across business units

Job Responsibilities

• Explore and implement new technologies, methodologies, and innovations in data and analytics.

• Conduct research and development to identify and apply cutting-edge AI and machine learning (ML) solutions.

• Drive the creation, building, and deployment of advanced data-driven solutions that address complex business challenges.

• Collaborate closely with other teams to ensure smooth transitions and effective support for newly developed solutions.

• Facilitate the integration of advanced analytics models and applications into everyday operational workflows.

• Drive research initiatives and pilot projects that promote a culture of innovation and continuous improvement within the organization.

• Lead the team in developing impactful AI/ML models and data-driven applications that meet business needs and performance standards.

• Partner with external experts and industry peers to stay informed of emerging trends and best practices.

• Champion the adoption of innovative technologies and methodologies across the firm, influencing a forward-thinking approach towards data and analytics

• Integrate advanced AI/ML solutions with agentic technologies (e.g. LangChain) and develop predictive models and autonomous agents that automate complex data tasks, streamline workflows, and empower users.

• Manage and build the semantic data layer, defining relationships among key business entities to fuel intelligent search, recommendation engines, and network analysis.

• Develop data-driven tools, dashboards, and analytical applications to enhance advisor efficiency and deepen client engagement

• Deliver end-to-end solutions for understanding and improving organizational engineering performance through the creation of core data assets and analytical dashboards.

• Oversee the design, deployment, and management of prompt-based models on LLMs for various NLP tasks in the financial services domain.

• Conduct and guide research on prompt engineering techniques to improve the performance of prompt-based models within the financial services field, exploring and utilizing LLM orchestration and agentic AI libraries.

• Collaborate with cross-functional teams to identify requirements and develop solutions to meet business needs within the organization.

Required qualifications, capabilities, and skills

• Minimum 10+ years of experience in data science, analytics, or a related field.

• Significant leadership experience in managing data science/R&D teams and driving technology innovation.

• Proven track record of working with AI, ML, and advanced analytics models in a large-scale enterprise environment.

• Strong proficiency in programming languages (e.g., Python) and data science frameworks (e.g. scikit-learn, PyTorch, etc.).

• Deep understanding of AI/ML algorithms, statistical modeling, and modern data platforms (e.g. Snowflake, Databricks).

• Experience with cloud-based data technologies and big data ecosystems

Preferred qualifications, capabilities, and skills

• Excellent leadership and team management skills with a strategic vision.

• Strong interpersonal, communication, and presentation abilities.

• Ability to collaborate effectively across cross-functional teams and mentor emerging talent

• Advanced degree (Master’s or Ph.D.) in Data Science, Computer Science, Mathematics, Engineering, or a related field is preferred