Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Create, develop, assess, and consistently monitor statistical and time series models, incorporating econometric techniques to forecast demand 23–36 months ahead.

• Quickly prototype and refine new models, methodologies, and analytical libraries.

• Evaluate the strengths and weaknesses of new statistical tools and methodologies.

• Thoroughly analyze data sources, modeling assumptions, and outcomes, recognizing risks, biases, and uncertainties.

• Track US passport demand, survey outcomes, policy changes, travel, economic, geopolitical, and other relevant trends.

• Investigate methods to utilize this data for forecasting impacts on passport demand.

• Convert complex analytical results into clear, actionable insights for both technical and non-technical audiences.

• Pursue innovative approaches while adhering to methodological rigor.

• Keep abreast of the latest technologies, tools, and best practices in forecasting, statistics, and data science.

• Identify customer needs and find ways to enhance value.

⛳️ Requirements

• An advanced degree (PhD or Masters) from an accredited institution in a data-related discipline.

• Proficient communication skills with senior leadership, colleagues, and staff across all levels.

• Extensive experience in statistical analysis and time series modeling, including econometric methods, seasonal regression, and various statistical models.

• Proven ability to critically assess models, data, and assumptions rather than relying solely on pre-packaged solutions.

• Strong problem-solving capabilities and comfort in navigating ambiguous or changing problem scenarios.

• Quick learner of new tools, frameworks, and technologies, applying them effectively.

• Demonstrated track record of independent work and ownership over analytical projects.

• Proficient in Python statistics and machine learning frameworks and libraries, such as statsmodels, pandas, numpy, xgboost, scipy, and matplotlib.

• Experience with STATA.

• Familiarity with time series methods, including ARIMA and VAR.

• Experience in applying machine learning models to time series analysis in data-limited environments.

• Knowledge of Bayesian statistical models in time series analysis.

• Experience utilizing AWS cloud environments, particularly serverless technologies, for data science tasks.

🏝️ Benefits

• Comprehensive health and wellness benefits.

• Opportunities for professional development and growth.

• Flexible working arrangements.

• Supportive and inclusive workplace culture.

• Competitive salary and performance-based incentives.