GigFinder.ai
Posted 14 days agoVerified live 2d ago
Applied Statistician, Forecasting & Simulation
Brief overview
Remote
MastersOr in progress
$90k–$130k/yrStated range
3+ yrsMinimum
Statistical ModelingForecastingTime Series AnalysisEconometricsPredictive ModelingRegressionStatistical InferenceModel ValidationSimulation and Scenario AnalysisUncertainty AnalysisPythonR
About the company
GigFinder.aiGigFinder.ai
GigFinder was founded on a simple premise: the traditional job search is broken.
Job description
Summary
LMI is a digital solutions provider focused on accelerating government impact through innovative technology and mission-ready solutions. The Applied Statistician, Forecasting & Simulation will develop, evaluate, and refine statistical, econometric, predictive, and simulation models to forecast passport demand, assess uncertainty, and analyze potential future scenarios. The role also involves validating models, analyzing demand drivers, monitoring forecast performance, and communicating findings to technical and nontechnical stakeholders.
Responsibilities
- Develop and maintain statistical, econometric, and time series models to forecast passport demand
- Apply forecasting methods such as regression, ARIMA, exponential smoothing, state space models, Bayesian methods, and other appropriate techniques
- Develop simulations and scenario analyses to evaluate uncertainty and potential future outcomes
- Perform model validation, backtesting, sensitivity analysis, residual analysis, and forecast error evaluation
- Analyze historical demand, survey data, economic indicators, demographics, travel trends, policy changes, and other potential demand drivers
- Evaluate model assumptions, data quality, structural changes, bias, and sources of uncertainty
- Compare alternative modeling approaches and recommend methods based on accuracy, interpretability, and statistical rigor
- Monitor actual demand against forecasts and identify opportunities to improve model performance
- Communicate methodology, assumptions, uncertainty, and analytical findings to technical and nontechnical stakeholders
- Maintain reproducible analytical workflows, model documentation, and technical artifacts
Skills
- Bachelor's degree in Statistics, Econometrics, Economics, Applied Mathematics, Operations Research, or another highly quantitative discipline
- Ability to operate efficiently using new and emerging tools of quantitative analysis
- Experience in statistical analysis, forecasting, econometrics, predictive modeling, or related quantitative analysis
- Strong knowledge of regression, probability, statistical inference, time series analysis, model validation, and uncertainty
- Experience developing and evaluating forecasting models using ARIMA, regression-based forecasting, exponential smoothing, state space models, or comparable methods
- Experience with simulation, scenario analysis, or probabilistic modeling
- Experience validating models through backtesting, sensitivity analysis, residual analysis, or out-of-sample testing
- Proficiency with Python, R, Stata, SAS, MATLAB, or comparable statistical tools
- Strong analytical, problem-solving, and communication skills
- Ability to independently structure and solve complex quantitative problems
- Master's degree or PhD in Statistics, Econometrics, Economics, Applied Mathematics, Operations Research, or a related discipline
- Experience with demand, economic, population, workload, or other longitudinal forecasting
- Experience with Bayesian methods, Monte Carlo simulation, multivariate time series, or advanced econometric techniques
- Experience analyzing survey data, including sampling, weighting, representativeness, and sampling error
- Experience with Python statistical libraries, Stata, or R
- Experience working with economic, demographic, travel, public policy, or government administrative data
- Experience developing or evaluating simulation models and scenario-based forecasts
- Experience supporting federal government customers
Qualifications
Must Haves
- Bachelor's degree in Statistics, Econometrics, Economics, Applied Mathematics, Operations Research, or another highly quantitative discipline
- Ability to operate efficiently using new and emerging tools of quantitative analysis
- Experience in statistical analysis, forecasting, econometrics, predictive modeling, or related quantitative analysis
- Strong knowledge of regression, probability, statistical inference, time series analysis, model validation, and uncertainty
- Experience developing and evaluating forecasting models using ARIMA, regression-based forecasting, exponential smoothing, state space models, or comparable methods
- Experience with simulation, scenario analysis, or probabilistic modeling
- Experience validating models through backtesting, sensitivity analysis, residual analysis, or out-of-sample testing
- Proficiency with Python, R, Stata, SAS, MATLAB, or comparable statistical tools
- Strong analytical, problem-solving, and communication skills
- Ability to independently structure and solve complex quantitative problems
Nice to Haves
- Master's degree or PhD in Statistics, Econometrics, Economics, Applied Mathematics, Operations Research, or a related discipline
- Experience with demand, economic, population, workload, or other longitudinal forecasting
- Experience with Bayesian methods, Monte Carlo simulation, multivariate time series, or advanced econometric techniques
- Experience analyzing survey data, including sampling, weighting, representativeness, and sampling error
- Experience with Python statistical libraries, Stata, or R
- Experience working with economic, demographic, travel, public policy, or government administrative data
- Experience developing or evaluating simulation models and scenario-based forecasts
- Experience supporting federal government customers
Benefits
- Remote work arrangement (US-Remote)