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About This Role
RELOCATION ASSISTANCE: Relocation assistance may be available
CLEARANCE REQUIRED FOR START: Yes
CLEARANCE TYPE: Secret
TRAVEL: Yes, 10% of the TimeDescription
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At Northrop Grumman, our employees have incredible opportunities to work on revolutionary systems that impact people's lives around the world today, and for generations to come. Our pioneering and inventive spirit has enabled us to be at the forefront of many technological advancements in our nation's history \- from the first flight across the Atlantic Ocean, to stealth bombers, to landing on the moon. We look for people who have bold new ideas, courage and a pioneering spirit to join forces to invent the future, and have fun along the way. Our culture thrives on intellectual curiosity, cognitive diversity and bringing your whole self to work — and we have an insatiable drive to do what others think is impossible. Our employees are not only part of history, they're making history.
Northrop Grumman Aeronautics Systems sector is seeking an Associate Data Scientist or a Data Scientist to join our team of qualified, diverse individuals. This position will be located in Palmdale, CA where technology and teamwork come together. The qualified applicant will become part of Northrop Grumman's Tooling organization working in a collaborative environment while promoting a positive and proactive teamwork environment.
Essential Job Functions:
Creates data mining architectures/models/protocols, statistical reporting, and data analysis methodologies to identify trends in large data sets. Analysis may have many applications such as to address a business issue or provide a competitive advantage for the organization. Requires strong statistical and data visualization skills. Experience with data analytics to create and implement data\-driven infrastructure to drive efficiency in our organization. Strong project management skills to drive tasks/projects to completion ensuring budget, schedule, and quality requirements are met. Ability to utilize schedule, cost, and performance data to create user\-friendly graphics or data visualization (charts, plots, infographics, animations). Ability to create data handling site on SharePoint for the Tooling Sector and support troubleshooting and edits as required. Assist cost account manager in establishing baselines for cost, schedule, and scope, and track actual performance against those measures. Analyze trends and variances to identify potential risks and issues and recommend corrective actions as needed. Develop, analyze, and maintain estimates to completion and perform monthly budget, EAC, actuals, and Variance Analysis for Leadership briefings. Tracking of weekly actuals against monthly/yearly targets and monthly maintenance of cost analysis reports.
Basic Qualifications for Associate Data Scientist (Level 1\):
- 0 Years experience with Bachelors in Science
- Ability to obtain and maintain a U.S. Government Secret clearance and Special Program Access within a reasonable period of time, as determined by the company to meet its business need
- Knowledge of data gathering, cleansing, and transformation techniques
- Capable of gathering large amounts of data, evaluating and identifying trends
- Capable of presenting data via MS PPT, excel, and other Office tools
- Familiarity with data evaluation tools such as MS Excel, VBA
- Ability to collaborate between self\-organizing and cross\-functioning teams
- Proficient in Microsoft Suite
- Intermediate to advanced Excel (Formula, Gantt charts, pivot tables, Slicer)
- Strong Communication Skills
- Self driven learner
Basic Qualifications for Data Scientist (Level 2\):
- 1 year of experience with Bachelors in Science; 0 Years with Masters
- Ability to obtain and maintain a U.S. Government Secret clearance and Special Program Access within a reasonable period of time, as determined by the company to meet its business need
- Knowledge of data gathering, cleansing, and transformation techniques
- Capable of gathering large amounts of data, evaluating and identifying trends
- Capable of presenting data via MS PPT, excel, and other Office tools
- Experience with data evaluation tools such as MS Excel, VBA
- Strong Communication Skills
- Advanced Excel (Formula, Gantt charts, pivot tables, Slicer)
- Capable of using Tableau to evaluate data and present
- Proficient in Microsoft Suite
- Self driven learner
Preferred Qualifications
- Active U.S. Government Secret clearance
- Experience with cost account management
- Hands\-on experience with core Python data science tools (Numpy, Pandas, Matplotlib, SciKit\-Learn, etc.)
- Hands\-on experience with deep learning libraries (TensorFlow, PyTorch, etc.)
- Experience with anomaly detection and synthetic data strategies for machine learning
- Knowledge of databases (SQL Server, AWS Databases (DynamoDB, RDS, or similar)) and schema
- Data engineering skillsets
- Experience with Generative AI tools and frameworks (Stable Diffusion, GPT, HuggingFace, etc.)
- Experience with computer vision (CNN, Transformer architectures) and image/video data preparation for machine learning
- Hands\-on experience with time series analysis and sequence modeling
- Experience configuring and extracting data from mixed\-reality platforms (HoloLens 2\)
- Experience with Cloud environments (Azure, AWS\-SageMaker, S3, etc.)
- Hands\-on experience with sensor deployments (IoT sensors) and automating data collection and processing in industrial settings
- Experience with dashboarding frameworks (Plotly Dash, Panel, Streamlit, Tableau, etc.)
- MLOps knowledge and experience executing the full machine learning lifecycle
- Experience configuring and extracting data from numerous data sources and bringing them together
- Experience with SharePoint and creating websites via SharePoint
- Agile development
- Experience with the following Techniques:
- Data pipelines using ETL (Extract, Transform, Load)
- Data visualization and transformation
- Version control systems
- Exploratory Data Analysis (EDA)
- Statistical Modeling
- Statistical Inference
- Predictive Modeling
Knowledge, Skills and Ability:
- Use and/or application of technical principles, theories, and concepts
- Demonstrates the skill and ability to perform professional tasks
- Software: VS Code, Apache Airflow, , Tableau, Confluence, Jira
Problem Solving
Develops recommended solutions to technical problems as assigned.
Discretion/Latitude
Work is reviewed for soundness of technical judgment, overall adequacy and accuracy. Works under general supervision.
Impact
Contributes to the completion of assigned technical tasks. Failure to achieve results should be detected in supervisory oversight.
Liaison
Contacts are primarily with immediate supervisor, project leaders, and other professionals in the section or group
Primary Level Salary Range: $83,800\.00 \- $125,800\.00
Secondary Level Salary Range: $101,000\.00 \- $151,400\.00
The above salary range represents a general guideline; however, Northrop Grumman considers a number of factors when determining base salary offers such as the scope and responsibilities of the position and the candidate's experience, education, skills and current market conditions.
Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay. Annual bonuses are designed to reward individual contributions as well as allow employees to share in company results. Employees in Vice President or Director positions may be eligible for Long Term Incentives. In addition, Northrop Grumman provides a variety of benefits including health insurance coverage, life and disability insurance, savings plan, Company paid holidays and paid time off (PTO) for vacation and/or personal business.
The application period for the job is estimated to be 20 days from the job posting date. However, this timeline may be shortened or extended depending on business needs and the availability of qualified candidates.
Northrop Grumman is an Equal Opportunity Employer, making decisions without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability, or any other protected class. For our complete EEO and pay transparency statement, please visit http://www.northropgrumman.com/EEO. U.S. Citizenship is required for all positions with a government clearance and certain other restricted positions.
Salary Context
This $83K-$151K range is in the lower quartile for Data Scientist roles in our dataset (median: $155K across 226 roles with salary data).
View full Data Scientist salary data →Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 3,708 AI roles we're tracking, Data Scientist positions make up 8% of the market. At Northrop Grumman, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $192,890 based on 463 positions with disclosed compensation. Entry-level AI roles across all categories have a median of $120,000. This role's midpoint ($117K) sits 39% below the category median. Disclosed range: $83K to $151K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Northrop Grumman AI Hiring
Northrop Grumman has 5 open AI roles right now. They're hiring across Data Scientist, Research Scientist, AI Software Engineer. Positions span Remote, US, Corinne, UT, US, Dulles, VA, US. Compensation range: $147K - $206K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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