Senior Officer, Modeling & Quantitative Science, Family Planning, 12-month LTE

Seattle, United States
negotiable Expires in 4 weeks

JOB DETAIL

The Foundation

We are the largest nonprofit fighting poverty, disease, and inequity around the world. Founded on a simple premise: people everywhere, regardless of identity or circumstances, should have the chance to live healthy, productive lives. We believe our employees should reflect the rich diversity of the global populations we aim to serve. We provide an exceptional benefits package to employees and their families which include comprehensive medical, dental, and vision coverage with no premiums, generous paid time off, paid family leave, foundation-paid retirement contribution, regional holidays, and opportunities to engage in several employee communities. As a workplace, we’re committed to creating an environment for you to thrive both personally and professionally.

The Team

The Gender Equality Division’s mission it to ensure women and girls in Africa and South Asia can enjoy good health, make their own choices, earn their own money, and be leaders in their societies. When women and girls have an equal chance to thrive and lead, everyone benefits. We know that women and girls are not a monolith. A woman’s experience and the barriers she faces are different depending on factors like where she lives, how old she is, and how much money her family has—alongside other factors including her race, caste, and education level. We seek to address these compounding barriers through deep partnership with our grantees. As a philanthropy, our role is to listen to and learn from these experts. We take risks in new areas, prove concepts, and bring these ideas to governments, partner organizations, and private sector companies to scale. The Gender Equality Division builds off our existing strengths as a foundation in areas like global health and data, partnering closely with all our global divisions.

This role is a part of the Gender Equality Division’s Family Planning (FP) team, which works to bring access to high-quality contraceptive information, services, and supplies to women and girls in the world’s poorest countries. The FP team’s work spans the spectrum from innovation, advocacy, and data, to supporting delivery and scale in localized and global contexts.

*This position is a limited-term position for 12 months. Relocation will not be provided.

Your Role
You are responsible for addressing significant science, policy, and operational questions and advising on decisions by modeling, conducting risk analyses, and assessing interventions. You create data and analytics that close gaps in primary data, strengthen analytical tools and methods used, and package and disseminate data and insights. You have an excellent ability to convert analytical work products into compelling visualizations, persuasive narratives, and novel insights with significant experience.

What You’ll Do

  • Support efforts with modeling, risk analysis, and assessment of interventions.
  • Identify impactful problems in control and elimination and address them by applying existing methods or developing novel methods as needed.
  • Envision innovative framings of problems to simplify work and cut to essential issues.
  • Work closely with internal and external partners to understand the current policy and program questions.
  • Develop and maintain productive and engaging collaborations with internal strategic partners.
  • Clearly communicate sophisticated methods to diverse audiences.
  • Identify knowledge or data gaps in settings in which we work and propose solution.
  • Support inclusive culture through modeling behaviors and actions; escalate issues in a timely fashion to appropriate stakeholders.

Your Experience

  • Master’s degree required, experience preferably in a quantitative field (e.g., Statistics/Biostatistics, Applied Mathematics, Economics, Epidemiology, Computational Biology).
  • Knowledge of disease control and public health issues in LMIC’s a plus; knowledge of polio modeling and eradication desired.
  • Proficiency in at least one scripting language (e.g., R or Python).
  • Demonstrated ability to work efficiently as part of a team.
  • Experience in statistical inference preferred (e.g., maximum likelihood, Bayesian statistics, optimization).
  • Strong data analysis skills.
  • Stochastic modeling or disease modeling experience (e.g., stochastic processes, compartmental models, or agent-based models).

*Must be able to legally work in the country where this position is located without visa sponsorship.

The salary range for this role is $182,600 to $283,100 USD. We recognize high-wage market differences in Seattle and Washington D.C., where our offices are located. The range for this role in these locations is $199,000 to $308,400 USD. As a mission-driven organization, we strive to balance competitive pay with our mission. New hire salaries are typically between the salary range minimum and midpoint. Actual placement in the range will depend on a candidate’s job-related skills, experience, and expertise, as evaluated during the interview process.

#LI-BR1

Hiring Requirements

As part of our standard hiring process for new employees, employment will be contingent upon successful completion of a background check.

Candidate Accommodations

If you require assistance due to a disability in the application or recruitment process, please submit a request here.

Inclusion Statement

We are dedicated to the belief that all lives have equal value. We strive for a global and cultural workplace that supports ever greater diversity, equity, and inclusion — of voices, ideas, and approaches — and we support this diversity through all our employment practices.

All applicants and employees who are drawn to serve our mission will enjoy equality of opportunity and fair treatment without regard to race, color, age, religion, pregnancy, sex, sexual orientation, disability, gender identity, gender expression, national origin, genetic information, veteran status, marital status, and prior protected activity.

Seattle, United States

location