Data Scientist –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 entry 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.

We are seeking a talented and driven Data Scientist to join our evolving and dynamic team. This position is open to candidates at entry 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.

As with any position, additional expectations exist. Some of these are, but are not limited to, adhering to normal working hours, meeting deadlines, following company policies as outlined by the Employee Handbook, communicating regularly with assigned supervisor(s), and staying focused on the assigned tasks including company meetings, and completing other tasks as assigned.

• Time Series & Mathematical Modeling:
  Support the development and evaluation of statistical and time series forecasting models, including ARIMA, Prophet, regression, and tree-based models.
• Data Pipeline Construction & Scripting:
  Write and maintain Python scripts to scrape, extract, clean, join, and transform structured and unstructured financial data from web sources, APIs, databases, and raw files.
• Model Validation & Quality Assurance:
  Execute established validation workflows, compare model performance using metrics such as RMSE, MAE, and MAPE, and identify potential data-quality or data-leakage issues.
• Quantitative Feature Engineering:
  Assist with analyzing historical pricing, inflation indices, budget cycles, and spending patterns to create features for forecasting models.
• Data Analysis & Documentation:
  Perform exploratory data analysis and document data sources, assumptions, transformations, model results, and known limitations.
• Stakeholder Communication:
  Create reports, visualizations, and summaries that explain analytical findings to technical and non-technical stakeholders.
• Resourcefulness & Learning:
  Learn new domain requirements, proprietary databases, customer tools, and forecasting methods with guidance from senior team members.
• 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.
• Recent graduates and candidates with up to two years of relevant professional, internship, research, or academic experience are encouraged to apply.
• Foundational knowledge of linear algebra, calculus, probability, and statistics.
• Working knowledge of Python for data manipulation and analysis, including pandas and Num Py.
• Academic, internship, research, or project experience involving statistical modeling, machine learning, predictive analytics, or time series forecasting.
• Basic understanding of single-variable and multi-variable forecasting methods.
• Understanding of model evaluation concepts, including…