Senior Director, Analytics & Modeling

I am currently working with a leading financial institution that's looking for a Senior Director to lead a high-impact team focused on the development, validation, and implementation of advanced statistical and machine learning models. Ideal candidates should have 10+ years in model development and analytics, proven leadership and team management skills, and proficiency in programming languages such as Python or R. This role is ideal for someone who not only brings deep technical expertise, but also has a strong track record of building, validating, and defending models in regulated environments. It requires a strategic thinker who can bridge the gap between analytics and business impact, and who is comfortable engaging with both internal leadership and external regulators.

Responsibilities:

• Lead a team of data scientists and statisticians in building and deploying predictive models, segmentation schemes, and analytical frameworks.
• Set the strategic direction for applying statistical and machine learning techniques to address complex organizational challenges.
• Ensure models are developed in alignment with regulatory standards and are defensible during audits and reviews.
• Collaborate with internal stakeholders to define modeling objectives, interpret results, and translate insights into actionable strategies.
• Serve as a subject matter expert in regulatory discussions, clearly articulating model rationale, methodology, and business impact.
• Oversee model validation, performance monitoring, and documentation to ensure transparency, accuracy, and ethical use.
• Partner with data engineering and IT teams to ensure data integrity, availability, and security for modeling initiatives.
• Establish and maintain best practices for model governance, lifecycle management, and compliance.

Qualifications:

• Advanced degree (Master's or Ph.D.) in Statistics, Mathematics, Data Science, or a related quantitative field.
• At least 10 years of experience in statistical modeling, machine learning, and data analytics, including leadership of technical teams.
• Proficiency in programming languages such as Python or R, and experience with statistical tools (e.g., SAS).
• Strong understanding of modeling techniques including regression, classification, clustering, and time series analysis.
• Demonstrated ability to communicate technical concepts to both technical and non-technical stakeholders.
• Experience working with model risk management teams and navigating regulatory environments.
• Proven track record of aligning modeling efforts with business goals and delivering measurable outcomes.

Preferred:

• Familiarity with big data platforms and cloud-based analytics environments.
• Knowledge of regulatory frameworks and compliance standards in highly regulated industries.
• Experience presenting to regulators or external auditors and defending model methodologies.