Data Scientist

This senior-level Data Scientist role supports the Department of State Passport Bureau (CA/PPT) by designing, developing, evaluating, and monitoring forecasting models for US passport demand. The position focuses on statistical and time series methods, including econometric approaches, and requires translating results into insights for both technical and non-technical stakeholders.

Role Summary

Develop forecasting models that project US passport demand 23 to 36 months into the future. The work includes prototyping new modeling strategies, assessing data quality and assumptions, and maintaining ongoing evaluation and monitoring as conditions and inputs change.

Key Responsibilities

• Design, develop, evaluate, and actively monitor statistical and time series models, including econometric approaches, to forecast demand 23 to 36 months ahead.
• Rapidly prototype and iterate on new models, methodologies, and analytical libraries that use advanced statistical and related tools; assess strengths and limitations.
• Critically evaluate data sources, modeling assumptions, and results; identify risks, biases, and sources of uncertainty.
• Actively monitor passport demand signals, survey results, policy developments, and travel, economic, geopolitical, and other trends; explore ways to use these inputs to forecast impacts.
• Translate complex analytical outcomes into clear, actionable insights for technical and non-technical stakeholders.
• Work independently to explore novel approaches while maintaining methodological discipline and healthy skepticism.
• Stay current on emerging technologies, tools, and best practices in forecasting, statistics, and data science.
• Explore customer needs and identify opportunities to add value.

Requirements

• Advanced degree (PhD or Masters) from an accredited college or university in a data-related field of study.
• Strong communication skills to coordinate with senior leadership, peers, and staff across all levels.
• Advanced experience in statistical analysis and time series modeling, including econometric techniques, seasonal regression, and other statistical models.
• Demonstrated ability to think critically about models, data, and assumptions rather than relying on off-the-shelf solutions.
• Strong problem-solving skills and comfort operating in ambiguous or evolving problem spaces.
• Ability to learn new tools, frameworks, and technologies quickly and apply them effectively.
• Proven track record of independent work and ownership of analytical projects.

Technologies

• Python, statsmodels, pandas, numpy, xgboost, scipy, matplotlib
• STATA
• ARIMA, vector autoregression (VAR)
• Bayesian statistical models
• Cloud environments, including serverless technologies in the AWS cloud

Desired Attributes

• Creative and innovative mindset with risk awareness and analytical rigor.
• Willingness to challenge existing approaches while maintaining sound methodology.
• Curiosity-driven learning with a pragmatic approach to adopting new technologies.
• Comfort iterating quickly, testing ideas, and discarding approaches that do not meet standards.
• Experience with Python statistics and machine learning framework and libraries, including statsmodels, pandas, numpy, xgboost, scipy, and matplotlib.
• Experience working with STATA.
• Experience applying time series statistical methods, including ARIMA and vector autoregression (VAR).
• Experience applying machine-learning models to time series analysis in data-poor environments.
• Experience applying Bayesian statistical models to time series analysis.
• Experience leveraging cloud environments for data science tasks, specifically using serverless technologies in the AWS cloud.

Location and Compensation

Location: Remote (remote).
Compensation: USD 90,000 to 150,000 per year.