Affordability Analyst/Acquisition Data Scientist
Listed on 2026-08-22
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IT/Tech
Data Analyst, Data Scientist, Data Science Manager, Data Engineering
Description
Are you seeking an opportunity to implement novel analytic process and methods that improve acquisition program cost and schedule execution?
DescriptionAre you seeking an opportunity to implement novel analytic process and methods that improve acquisition program cost and schedule execution?
Are you motivated by taking disparate data sources and building structured analytic frameworks that support important resource allocation decisions?
If so, we're looking for someone like you to join our team at APL!
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., Dev Ops) of financial and parametric data in order to generate credible cost and schedule estimates.
You'll be joining a hardworking team of analysts who incorporate affordability and cost considerations into the critical solutions to the critical challenges our nation faces. As a member of our team, you will contribute to network-based schedule risk assessments, trade space studies (e.g., Analysis of Alternatives, Business Case Analyses, Economic Analyses), affordability studies (e.g., Life Cycle Cost Estimates, Total Ownership Costs), and earned value management (EVM) forecasting.
Asan Affordability Analyst/Acquisition Data Scientist, you will...
- Be responsible for aggregating cost and parametric data of government projects through both structured (DAMIR, CADE, VAMOSC, USA Spending.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 (Data Ops) 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.
You meet our minimum qualifications for the job if you...
- 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 [Sci Py, iGraph, Stats models, PyMC, NumPY], R, Stata, SAS, JMP, MATLAB, @Risk etc.).
- Are able to obtain an Interim Secret level security clearance by your start date and can ultimately obtain a Secret level clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship.
- Have a Master's degree, or Ph.D, 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.
The Johns Hopkins University Applied Physics Laboratory (APL) brings world-class…
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