Data Scientist Ii–Financial & Time Series Forecasting

Job Summary

We are seeking a talented and driven Data Scientist to join our evolving and dynamic team. This position is open to candidates at Mid to Senior level of experience who possess a strong mathematical foundation and a passion for predictive modeling. In this role, you will build, validate, and maintain multi-variable time series forecasting models to project financial data and agency expenditures over multi-year horizons.

You will work directly with financial records, taking ownership of the data lifecycle, from scraping, joining, and transforming raw datasets to rigorous model validation. We are looking for a resourceful problem-solver who excels at mathematical modeling, adapts quickly to changing data environments, and ensures our predictive tools remain accurate and resilient.

• 100% ON-SITE Norco, CA*

We are seeking a talented and driven Data Scientist to join our evolving and dynamic team. This position is open to candidates at Mid to Senior level of experience who possess a strong mathematical foundation and a passion for predictive modeling. In this role, you will build, validate, and maintain multi-variable time series forecasting models to project financial data and agency expenditures over multi-year horizons.

You will work directly with financial records, taking ownership of the data lifecycle, from scraping, joining, and transforming raw datasets to rigorous model validation. We are looking for a resourceful problem-solver who excels at mathematical modeling, adapts quickly to changing data environments, and ensures our predictive tools remain accurate and resilient.

• Time Series & Mathematical Modeling:
  Independently develop, compare, validate, and maintain advanced single-variable and multi-variable forecasting models using methods such as ARIMA, Prophet, regression, exponential smoothing, and tree-based models.
• Data Pipeline Construction & Scripting:
  Design and maintain modular Python scripts and data pipelines to scrape, extract, clean, join, validate, and transform structured and unstructured financial data.
• Model Validation & Quality Assurance:
  Design and execute backtesting, time-based cross-validation, regression testing, and model-monitoring workflows to ensure accuracy when code or data inputs change.
• Quantitative Feature Engineering:
  Analyze historical pricing, inflation indices, economic indicators, budget cycles, and spending patterns to develop statistically and economically defensible features.
• Model Performance & Risk Analysis:
  Evaluate forecast performance using RMSE, MAE, MAPE, bias, benchmark comparisons, and prediction intervals while preventing data leakage and look-ahead bias.
• Technical Ownership:
  Document model assumptions, limitations, data dependencies, validation results, and recommended uses of model outputs.
• Stakeholder Communication:
  Translate complex modeling results into clear reports, visualizations, recommendations, and leadership briefings.
• Technical Guidance:
  Provide technical support, code reviews, and guidance to junior Data Scientists or analysts as assigned.
• Resourcefulness & Learning:
  Evaluate new forecasting, statistical, AI, and machine-learning approaches and recommend improvements to analytical workflows.
• Compliance & Security:
  Maintain strict compliance with defense security protocols, confidentiality guidelines, and internal data handling policies.

• Bachelor’s degree in Mathematics, Statistics, Computer Science, Data Science, Economics, Finance, Engineering, or a related quantitative field and at least three years of relevant professional experience.
• A Master’s or Ph.D. degree in a related quantitative field may substitute for a portion of the professional experience requirement.
• Strong mathematical foundation in linear algebra, calculus, probability, statistics, and hypothesis testing.
• Professional proficiency in Python for data manipulation, statistical modeling, time series forecasting, and automation scripting.
• Demonstrated professional experience developing and validating predictive or time series forecasting…