Affordability Analyst/Acquisition Data Scientist

About the role

We are seeking an Acquisition Data Scientist to help develop next-generation project management cost and schedule control techniques across the full data science pipeline in support of DoW / US Govt. Sponsors. Significant tasks will include the collection, pre-processing, normalization, statistical analysis, and development operations (e.g., DevOps) of financial and parametric data in order to generate credible cost and schedule estimates.

Responsibilities

• Be responsible for aggregating cost and parametric data of government projects through both structured (DAMIR, CADE, VAMOSC, USASpending.gov) and unstructured (open-source web website, LLMs, domain expert interviews) research in order to improve upon existing or generate new and innovative cost estimating relationships.
• Contribute to studies that quantify best value assessments through affordability analysis, decision frameworks, data visualization, sensitivity analysis, and data management.
• Learn to build cost and schedule estimates integrating statistical analysis, network science, modeling & simulation (M&S), cost databases, and expert opinion in Excel, MATLAB, Python, R, and cost estimating software (e.g., ACEIT and Price Trueplanning).
• Design, implement, and operationalize data operations (DataOps) pipelines that support scalable, and reliable data analytics across defense acquisition programs.
• Collaborate with APL staff from all sectors and departments on technical studies across land, sea, air, space, and cyberspace domains.

Requirements

• Have a Bachelor's degree in data science, business analytics, statistics, economics, computer science, mathematics, engineering, operations research, or a related field.
• Have proven experience organizing data into flexible, scalable, and reusable structures, performing comprehensive data analysis, and establishing data management frameworks.
• Have proficient software programming capabilities in Python and SQL.
• Have knowledge of at least several statistical analysis and simulation packages (Python [SciPy, iGraph, Statsmodels, PyMC, NumPY], R, Stata, SAS, JMP, MATLAB, @Risk etc.).
• Able to obtain an Interim Secret level security clearance by your start date and can ultimately obtain a Secret level clearance.

Qualifications

• Have a Bachelor's degree in data science, business analytics, statistics, economics, computer science, mathematics, engineering, or operations research.
• Have proficient software programming capabilities in Java, JavaScript, and/or C++.
• Have a certification related to cost analysis (DAWIA or CCEA) and/or earned value management (EVMP).
• Have domain expertise in creating data analysis dashboards through Shiny, Python, JavaScript, CSS, Visual Basic, Tableau, etc.