Director, Optimization Analyst

Jobgether SRL; United States; Remote; USD 88,000 - 140,000; Full time

Benefits offered by this job

Remote-first work

Bonus opportunities

Comprehensive benefits

Career growth

Job summary

Jobgether SRL seeks a Director, Optimization Analyst to lead strategic analytics for digital assessment operations in the United States. The role combines hands-on modeling with executive influence, shaping forecasting, optimization, simulation, and decision-support solutions that improve efficiency, scale, and customer experience.

You will build end-to-end models, develop AI-enabled tools, and drive an analytics roadmap across Operations, Product, Finance, and customer-experience teams.

Qualifications

• 5–7+ years of practical data analytics experience.
• Bachelor’s degree in business, engineering, economics, or quantitative discipline; master’s preferred.
• Advanced analytical capabilities in forecasting, statistical analysis, cost assessment, and decision support.
• Strong experience with predictive modeling, optimization, forecasting, and related quantitative methods.
• Demonstrated ability to apply analytics to operational efficiency or customer experience.
• Proven track record of delivering measurable improvements through data-driven solutions.
• Experience in government, education, technology, services, or other complex environments is valuable.
• Excellent written and verbal communication skills with cross-functional collaboration.

Responsibilities

• 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 to improve efficiency and reduce cost.
• Build demand-forecasting pipelines that improve accuracy, scalability, and turnaround time.
• Develop real-options and capacity optimization models that minimize costs while preserving flexibility.
• Model operational and financial impact of policy changes to support informed decisions.
• Create analytics reporting and dashboards for visibility into key metrics and faster decisions.
• Research and adopt modern analytical approaches, including AI-assisted coding and data synthesis.
• Improve reliability, maintainability, and reusability of models for evolving conditions.
• Partner with cross-functional teams to embed analytics into decision-making.
• Analyze customer-flow and cross-program challenges to reduce friction and improve experience.
• Collaborate on budget assumptions, cost drivers, and variance tracking to reflect constraints.
• Translate complex findings into clear recommendations for stakeholders.
• Shape the analytics roadmap by identifying high-value opportunities and advising leadership.

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Director, Optimization Analyst based in United States.

This is a strategic analytics leadership role focused on improving the efficiency, scalability, and customer experience of digital assessment operations.

You will build and own sophisticated forecasting, optimization, simulation, and decision-support models from concept through deployment.

Your work will help organizations make smarter operational and financial decisions while reducing cost, friction, and resource constraints.

You will collaborate closely with Operations, Product, Program, Technology, Finance, and customer-experience teams to turn complex challenges into measurable outcomes.

The role combines hands-on analytical development with strategic influence, requiring both technical depth and strong business judgment.

You will also help shape the analytics roadmap, introduce modern tools and AI-enabled approaches, and strengthen the reliability of analytical solutions.

This is an opportunity to use advanced data and optimization techniques in a mission-driven environment where better decisions can create meaningful impact for millions of learners.

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.

How Jobgether Works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.