Affordability Analyst/Acquisition Data Scientist

Johns Hopkins Applied Physics Laboratory•Laurel, MD

8h•Onsite

About The Position

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. 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.

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.).
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.

Nice To Haves

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.

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.