Director, Optimization Analyst

Accountabilities: Own demand forecasting and capacity optimization models end to end, including methodology selection, development, validation, deployment, and ongoing improvement. Develop forecasting, optimization, simulation, predictive, and cost-assessment models that improve operational efficiency and reduce cost and friction. Build demand-forecasting pipelines that improve accuracy, scalability, and turnaround time for digital assessment operations. Develop real-options and capacity optimization models that minimize committed costs while preserving the flexibility to respond to changing demand. Model the operational and financial impact of potential policy and program changes to support informed decision-making. Create analytics reporting and dashboards that provide stakeholders with visibility into key operational metrics and enable faster decisions. Research and adopt modern analytical approaches and technologies, including AI-assisted coding and data synthesis, to increase productivity and analytical scale. Improve the reliability, maintainability, and reusability of models so that analysis can be trusted and repeated as operational conditions evolve. Partner with Product, Program, Operations, Technology, Finance, and customer-experience teams to embed analytics directly into operational decision-making. Analyze customer-flow and cross-program challenges to identify opportunities for reducing friction and improving the overall experience. Collaborate with Finance and Program stakeholders on budget assumptions, cost drivers, and variance tracking to ensure models reflect real-world financial constraints. Translate complex analytical findings into clear recommendations that directly influence operational and strategic decisions. Shape the analytics roadmap by identifying high-value modeling opportunities and advising leadership on feasibility, sequencing, and trade-offs. Turn ambiguous operational problems into structured analytical approaches, even when no established methodology or playbook exists. Requirements 5–7+ years of practical data analytics experience, including experience leading analytics initiatives in a professional environment. Bachelor’s degree in business, engineering, economics, or another quantitative discipline; a master’s degree in a quantitative field is preferred. Advanced analytical capabilities in forecasting, statistical analysis, cost assessment, and decision support. Strong experience with predictive modeling, optimization, forecasting, statistical analysis, or related quantitative methods. Demonstrated ability to apply analytics to operational efficiency, customer experience, process improvement, or complex business challenges. Proven track record of delivering measurable business or operational improvements through data-driven solutions. Experience working in government, education, technology, services, or another operationally complex environment is valuable. Strong ability to translate technical analysis into concise, actionable recommendations for business and operational stakeholders. Excellent written and verbal communication skills, with the ability to collaborate effectively across functions and organizational levels. Curiosity about emerging technologies and willingness to experiment with and independently learn new AI-enabled analytical tools. Strong problem-solving skills, a growth mindset, and the ability to work effectively with ambiguity. Collaborative and empathetic approach, with the ability to build trust, incorporate diverse perspectives, and contribute to shared outcomes. Ability to travel approximately 4–6 times per year for business meetings or visits to organizational offices. Authorization to work in the United States. Benefits Remote-first role within the United States, with hybrid flexibility available near designated offices. Annual base salary range of $88,000–$140,000 , adjusted according to location, experience, qualifications, and internal equity. Compensation approach designed around transparency, market data, qualifications, and impact. Potential for annual bonuses and merit-based salary increases and promotions. Comprehensive benefits package designed to support employee well-being and professional growth. Mission-driven work where analytics directly contributes to improving educational and career opportunities. Supportive team environment with investment in employee development and long-term career growth. Opportunities to work with emerging technologies, AI-driven solutions, advanced analytics, and modern data practices. Flexibility to work remotely, with occasional in-person collaboration and business travel.