Director, Optimization Analyst

Team: Analyst

Location: US

Commitment: Full-time

Workplace Type: remote

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.