Data Scientist II - Financial & Time Series Forecasting

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.

What You Will Do

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. Design and maintain modular Python scripts and data pipelines to scrape, extract, clean, join, validate, and transform structured and unstructured financial data.

Why It Might Be a Fit

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. Strong verbal and written communication skills with the ability to explain mathematical models, assumptions, risks, and results to non-technical stakeholders.

Requirements

• US Citizenship Required
• Ability to obtain and maintain a Secret Security Clearance
• 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.
• 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 models.
• Demonstrated knowledge of both single-variable and multi-variable forecasting methods.
• Experience with backtesting, time-based cross-validation, model benchmarking, and error-metric evaluation.
• Strong understanding of data leakage, look-ahead bias, overfitting, feature stability, and model uncertainty.
• Experience developing clean, modular, documented, and maintainable analytical code.
• Ability to independently investigate data-quality, pipeline, or model-performance issues.

Benefits

• medical, dental, and vision insurance
• life insurance
• long and short-term disability
• Health Savings Account
• Flexible Spending Account
• 401K Retirement Plan options
• Tuition Reimbursement
• assorted voluntary benefits