Lockheed Martin Data Science in 2026

Lockheed Martin has made artificial intelligence and machine learning central to its defense technology strategy, investing billions of dollars in AI-enabled systems across its four business areas. In 2026, the company employs hundreds of data scientists, ML engineers, and AI researchers who apply advanced analytics to some of the most complex problems in national security. From predictive maintenance algorithms for the F-35 fleet to autonomous target recognition for satellite imagery, data science at Lockheed Martin operates at the intersection of cutting-edge technology and consequential real-world applications. This guide covers the roles available, salary expectations, required skills and clearances, tools and technologies, and how to build a data science career at one of the world's largest defense contractors.

The Role of Data Science at Lockheed Martin

Data science at Lockheed Martin is not academic research — it is applied engineering focused on delivering capabilities to military and intelligence customers. The work spans four primary domains:

Predictive Analytics and Maintenance

Data scientists build models that predict component failures before they occur, optimizing maintenance schedules for military platforms. For the F-35 program alone, predictive maintenance algorithms process telemetry from a global fleet to reduce downtime and lower lifecycle costs. This work directly affects aircraft availability and mission readiness.

Computer Vision and Image Intelligence

ML engineers develop algorithms for processing satellite imagery, sensor data, and full-motion video. These systems perform automatic target recognition, change detection, and pattern-of-life analysis across vast datasets. Much of this work supports intelligence community customers and requires high-level security clearances.

Natural Language Processing and Intelligence Analysis

NLP systems help analysts process massive volumes of text data — signals intelligence reports, open-source intelligence, and multi-language communications. Data scientists build models that extract entities, detect sentiment, and identify connections across documents.

Autonomous Systems

AI/ML capabilities underpin the next generation of autonomous military systems — from uncrewed aerial vehicles to robotic ground platforms to autonomous undersea systems. Data scientists develop the perception, decision-making, and navigation algorithms that enable these platforms to operate in contested environments.

Available Roles and Salary Ranges

Lockheed Martin offers data science positions across multiple experience levels and specializations:

The median yearly compensation for data scientists at Lockheed Martin is approximately $190,000, including base salary, bonuses, and long-term incentives. Entry-level roles (E1) start around $83,000, while the most senior individual contributor positions (E6) can reach $278,000.

AI/ML Engineers average $149,548 per year, with the typical pay range between $120,090 and $189,567 depending on experience, clearance level, and geographic location.

Tools and Technology Stack

Lockheed Martin's data science teams work with a mix of standard industry tools and defense-specific platforms:

Programming Languages

• Python — Primary language for data science and ML development
• R — Used in some statistical analysis and research contexts
• C++ — Performance-critical ML inference on embedded platforms
• Java/Scala — Big data processing pipelines and Spark applications
• MATLAB — Signal processing and engineering analysis

ML Frameworks and Libraries

• PyTorch — Preferred deep learning framework for research and production
• TensorFlow — Used in some production ML systems
• scikit-learn — Classical ML algorithms and feature engineering
• OpenCV — Computer vision applications
• Hugging Face — NLP model development and fine-tuning
• ONNX — Model format for cross-platform deployment

Data and Infrastructure

• Apache Spark — Distributed data processing for large-scale analytics
• Kubernetes — Container orchestration for ML model deployment
• GPU clusters — NVIDIA A100/H100 for training large models
• Cloud platforms — AWS GovCloud, Azure Government for approved workloads
• Palantir — Used on some intelligence community programs
• Custom classified platforms — Proprietary tools for handling classified data

Security Clearance Requirements

Clearance requirements vary by role and program:

Lockheed Martin sponsors clearance processing for new hires, but the timeline can significantly affect start dates. Candidates who already hold active clearances — particularly from military service or other defense contractors — have a significant competitive advantage.

Some positions are explicitly posted as requiring existing TS or TS/SCI clearance, while others indicate clearance as a preferred qualification with the expectation that the company will sponsor processing.

Locations for Data Science Roles

Lockheed Martin data science positions are distributed across multiple locations:

• Herndon, VA — AI/ML engineering near the intelligence community
• Annapolis Junction, MD — Classified data science near NSA
• Orlando, FL — Missiles and Fire Control analytics
• Fort Worth, TX — F-35 program data and predictive maintenance
• Denver/Littleton, CO — Space program data science
• Sunnyvale, CA — Satellite systems and space intelligence
• King of Prussia, PA — Rotary and Mission Systems

The highest concentration of data science roles is in the Washington DC metro area, where proximity to intelligence community customers drives demand.

Qualifications

Required

• Bachelor's degree in computer science, data science, statistics, mathematics, physics, or engineering
• Proficiency in Python and at least one ML framework (PyTorch or TensorFlow)
• Experience with statistical analysis and machine learning algorithms
• U.S. citizenship (required for clearance eligibility)
• Ability to obtain and maintain security clearance

Preferred

• Master's or PhD in a quantitative discipline
• Published research in ML, computer vision, or NLP
• Experience with deep learning architectures (CNNs, transformers, GANs)
• Familiarity with MLOps practices (model monitoring, CI/CD for ML)
• Prior experience in defense or intelligence community
• Active security clearance (TS or TS/SCI)

Certifications That Help

• AWS Certified Machine Learning — Specialty
• Google Professional Machine Learning Engineer
• NVIDIA Deep Learning Institute certifications
• CompTIA Security+ (often required for DoD IT work)

Career Path

Data science career progression at Lockheed Martin follows the company's standard engineering ladder:

Level 1-2 (Entry): Data analyst or junior data scientist. Focus on data preparation, exploratory analysis, and implementing existing algorithms. Salary: $83K-$130K.

Level 3 (Mid): Data scientist or ML engineer. Own end-to-end model development for specific applications. Begin mentoring junior team members. Salary: $130K-$190K.

Level 4 (Senior): Senior data scientist or senior ML engineer. Technical lead for complex ML systems. Drive architecture decisions and best practices. Salary: $170K-$230K.

Level 5-6 (Staff/Principal): Staff AI research engineer or principal data scientist. Set technical direction for multiple programs. Influence company AI strategy. Salary: $220K-$278K.

Management Track: ML engineering manager, AI program manager, director of data science. Manage teams and budgets. Salary: $180K-$300K+.

Lockheed Martin vs. Tech Companies for Data Science

A common question from data scientists is whether they should pursue defense or commercial technology careers:

The defense data science career offers a unique value proposition: the work is consequential, the security clearance creates a durable competitive advantage, and the programs are long-term. However, compensation at Big Tech companies typically exceeds defense contractor pay significantly, and the pace of innovation is faster in commercial settings.

For candidates who are motivated by national security mission and value stability, Lockheed Martin is an excellent choice. Browse current data science jobs and machine learning jobs in the space industry on Zero G Talent.

Frequently Asked Questions

Can I do data science at Lockheed Martin without a clearance?

Some entry-level positions allow you to start while clearance processing is underway, working on unclassified tasks during the interim. However, the majority of data science roles require at least Secret clearance to be fully productive, and many require TS/SCI.

Does Lockheed Martin support PhD programs while working?

Yes. Lockheed Martin's tuition reimbursement program covers up to $10,000 per year for graduate studies. Some employees pursue part-time PhD programs at nearby universities while working full-time. The company also partners with universities on research projects.

What programming languages are most important?

Python is the primary language for data science at Lockheed Martin, followed by C++ for embedded ML applications. Familiarity with SQL, Spark, and at least one deep learning framework (PyTorch preferred) is expected.

How does the compensation compare to other defense contractors?

Lockheed Martin's data science salaries are broadly competitive with Northrop Grumman, Raytheon, and L3Harris. Some smaller defense AI firms (like Palantir, Anduril, or Scale AI) may offer higher compensation through equity, but Lockheed Martin provides greater stability and a wider range of programs.

Can I publish research while working at Lockheed Martin?

Publication opportunities exist but are more limited than in academia or commercial tech. Work on classified programs cannot be published. However, Lockheed Martin does support publications on unclassified research and encourages conference participation at venues like NeurIPS, CVPR, and AAAI.