Data Scientist - E2 at Lockheed Martin

Department: GRS/Core-LMLS Aero Segment

Compensation

$81,100 – $150,500/yr

Setup: Hybrid
Location: Fort Worth, Texas
Type: Full-time
Level: not_specified
Posted: Sep 8, 2026

Description

Lockheed Martin is hiring a Data Scientist to support the F-35 Sustainment program by performing modeling, simulation, statistical and risk analysis, life-cycle cost analysis, performance and cost trade-offs, and business case analysis. The role involves collecting, processing, and analyzing data; developing immersive stories; building data models and discrete-event simulators; forecasting and root-cause analysis; and translating insights into business actions. Candidates need a bachelor's degree in engineering, physics, data science, mathematics, or a related technical discipline, experience with predictive and prescriptive modeling, Python or another high-level language, distributed databases, and data visualization, along with strong statistical and analytical skills.

Required Skills

Python
Tableau
Statistical analysis
Data visualization
Discrete-event simulation
Machine learning
Distributed databases
Time-series forecasting
SQL
MATLAB

Additional Information

Minimum Education: Bachelor of Science degree in Engineering, Physics, Data Science, Data Analysis, Mathematics, or a related technical discipline with an emphasis on modeling, data manipulation, and mathematical or statistical methods.
Required Previous Experiences: Experience with descriptive, predictive, prescriptive, and/or optimization modeling.
Experience constructing and executing data models and discrete-event simulators.
Experience with quantitative and qualitative data collection, cleaning, and management.
Experience with distributed databases and large datasets.
Programming experience with Python or another high-level language.
Experience with continuous improvement opportunities.
Experience analyzing supply chain networks.
Preferred Qualifications: Advanced statistics and statistical modeling.
Prescriptive analytics.
Time-series analysis and forecasting.
Proficiency with R, SAS, Python, MATLAB, SQL, Alteryx, and Tableau.
Knowledge of the SAFe agile framework and product owner support.
Ability to define technical solutions against business opportunities.
Experience applying scientific methods for testing, debugging, problem resolution, and root-cause analysis.
Experience deconstructing complex operations into component data problems for distributed team work.
Experience with data structures and hierarchies.
Experience collecting and compiling datasets from disparate sources.
Proficiency with the Microsoft Office suite.
Experience managing data quality and configuration control.