Senior Director, Data Science and AI Agents

Job description

Senior Director, Data Science Location: Bay Area preferred, optional: Nashville, TN or Sterling, VA POSITION OVERVIEW The Senior Director of Data Science leads enterprise data science strategy, delivery, and governance to drive measurable business impact. This role oversees teams building predictive, optimization, and generative models, partnering with cross-functional leaders to prioritize high-value use cases. The leader establishes enterprise best practices for model development, MLOps, and responsible AI, and ensures outcomes align with corporate goals, risk standards, and compliance. The role balances long-term platform investments with near-term initiatives, fosters talent development, and communicates complex insights clearly to executives. Success is measured by adoption, ROI, and operational reliability of data science solutions. ESSENTIAL JOB SKILLS/DUTIES Own enterprise data science strategy and multi-year roadmap. Prioritize high-impact use cases with executive stakeholders. Oversee model lifecycle, from discovery to productionization. Establish enterprise level standards for MLOps and responsible AI governance. Develop talent, structure teams, and manage budgets. Communicate results and risks to senior leadership. REQUIRED TECHNICAL SKILLS Data Mining: Applying techniques to extract patterns, relationships, and insights from structured and unstructured data. Data Modeling: Designing structured representations of data, including entities, relationships, and attributes, to support analysis and system design. Data Visualization: Presenting data through visual formats such as charts, graphs, maps, and dashboards to communicate insights and trends. Experimental Design: Designing and structuring experiments, including variable selection, control groups, and bias mitigation methods, to produce valid and reliable results. Machine Learning: Developing and applying machine learning models, including deep learning approaches, to generate predictions and classifications. Predictive Modeling: Building statistical and mathematical models using historical data to forecast outcomes and identify trends. Business Intelligence Technologies: Using tools and platforms to collect, process, analyze, and display data through reporting and dashboard solutions. Programming Languages: Writing and maintaining code to develop analytical models, scripts, and data-driven applications. Mathematical Modeling: Creating mathematical representations of real-world problems to support analysis and predictive insights. Generative Artificial Intelligence: Developing and applying generative models to create original outputs based on learned data patterns. REQUIRED SOFT/LEADERSHIP SKILLS Executive communication and storytelling with data. Stakeholder influence and strong cross-functional relationship building. Strategic planning and portfolio prioritization discipline. People leadership, coaching, and succession planning. Change management and adoption enablement. REQUIRED EDUCATION & EXPERIENCE Advanced degree in quantitative field or equivalent experience. 12+ years in data science or advanced analytics. 7+ years leading teams and complex programs. Proven delivery of measurable business outcomes. PREFERRED EDUCATION & EXPERIENCE Masters in statistics, computer science, or related discipline. Leadership experience in large, matrixed organizations. Track record scaling platforms and reusable assets. PREFERRED LICENSES/CERTIFICATIONS Cloud certification in AWS, Azure, or Google Cloud. Certification in ML or MLOps frameworks. Responsible AI or model risk management accreditation.