Sr Director I, Data Science

Technical Advisory & Quality Assurance Serve as a senior technical reviewer across active modeling projects, identifying structural risks before they become production problems — including data leakage, label construction errors, distribution shift, and flawed evaluation methodology. Challenge assumptions at the design stage: scrutinize feature selection rationale, target variable definitions, train/test splits, and deployment contexts to surface gaps in problem framing. Conduct focused reviews of model documentation, validation approaches, and monitoring frameworks; provide specific, actionable feedback rather than general guidance. Recognize when a modeling approach is fundamentally misaligned with the underlying business question and redirect teams toward higher-value formulations. Mentor data scientists and senior modelers across USDS — providing technical expertise, business acumen, and systems thinking in roughly equal measure. Help develop the broader DS community's shared standards: code review practices, modeling documentation norms, reproducibility expectations, and peer review culture. Model intellectual rigor and intellectual humility: demonstrate what good technical judgment looks like, especially in the face of ambiguity or organizational pressure to move fast. Deep knowledge of predictive analytic techniques and statistical diagnostics of models. Expert knowledge of predictive toolset, to include highly technical tools. Proven ability to lead and drive projects and assignments to completion through others. Exchanges ideas and conveys complex information clearly and concisely, verbally, visually (presentations and exhibits), and in writing, consistent with the audiences and stakeholders with which they interact up to and including SBU/Corp Dept leadership. Exceptional interpersonal and communication skills required to establish and build effective relationships within and outside the aligned functional area and client group. Ability to give effective training and presentations to all levels of the organization. Interacts with senior executives. Demonstrated ability to anticipate areas of senior management concern, integrate different perspectives, and respond accordingly. Deep knowledge of business drivers and market context. Deep understanding of insurance operations and the procedures of Financial, Underwriting, Claims, Statistical, Information Technology, Legal and Sales departments. Utilizes significant business experience and judgment to direct work of unit and communicate results. Has a value-driven perspective with regard to understanding of work context and impact Competencies typically acquired through a PhD degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and 8 years of relevant experience, a Master`s degree (scientific field of study) and 10 years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) and 14 years of relevant experience. Insurance or financial services industry experience preferred.