[Remote] Data Scientist
Note: The job is a remote job and is open to candidates in USA. LMI is a digital solutions provider delivering innovative, mission-ready technology and AI solutions to federal agencies. The Senior Data Scientist will develop, evaluate, and refine statistical, econometric, and time series models to forecast passport demand for the Department of State Passport Bureau, while translating complex findings into actionable insights for stakeholders.
Responsibilities
- Design, develop, evaluate, and actively monitor statistical and time series models (including econometric approaches) for accurately forecasting demand 23-36 months into the future
- Rapidly prototype and iterate on new models, methodologies, and analytical libraries that rely on cutting edge statistical and other tools. Assess their strengths and limitations
- Critically evaluate data sources, modeling assumptions, and results, identifying risks, biases, and sources of uncertainty
- Actively monitor US passport demand; survey results; policy developments; travel, economic, geopolitical, and other trends; and creatively explore means of using these data to forecast impacts on passport demand
- Translate complex analytical findings into clear, actionable insights for technical and non-technical stakeholders
- Work independently to explore novel approaches while applying healthy skepticism and methodological discipline
- Stay current with emerging technologies, tools, and best practices in forecasting, statistics, and data science
- Explore customer needs and help identify ways to add value
Skills
- Advanced degree (PhD or Masters) from an accredited college or university in a data-related field of study
- Ability to communicate well with senior leadership, peers, and staff at all levels to facilitate excellent teamwork
- 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 working 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
- Creative and innovative mindset, balanced by risk awareness and analytical rigor
- Willingness to challenge existing approaches and push boundaries while maintaining methodological soundness
- Curiosity-driven learner with a pragmatic approach to adopting new technologies
- Comfortable iterating quickly, testing ideas, and discarding approaches that do not meet standards
- Experience in Python statistics and machine learning framework and libraries, including statsmodels, pandas, numpy, xgboost, scipy, matplotlib
- Experience working with STATA
- Experience applying statistical methods (time series analysis) including autoregressive integrated moving average (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
Benefits
- Remote work arrangement (US-Remote)
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