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About This Role
RELOCATION ASSISTANCE: No relocation assistance available CLEARANCE REQUIRED FOR START: No CLEARANCE TYPE: Secret TRAVEL: Yes, 10% of the TimeDescription
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 Mission Systems is a trusted provider of mission-enabling solutions for global security. We have a wide portfolio of secure, affordable, integrated, and multi-domain systems and technologies. Our differentiated battle management and cyber solutions deliver timely, mission-enabling information and provide superior situational awareness and understanding to protect the U.S. and its global allies.
Northrop Grumman Mission Systems is looking for you to join our team as a Data Scientist for our Advanced Packaging Technology µ-Line based in Apopka, Florida.
Northrop Grumman’s semiconductor foundry, packaging, integration, and test lines have unique capabilities of supporting a range of production microelectronics and providing leading-edge technology development.
The Apopka Florida wafer bumping µ-Line supports flip chip, 2.5D, and 3D packaging for internal and external production customers as well as emerging technology programs. The line provides a range of bump compositions and processes that include photo, sputter, electro-plating, AOI, and solder-sphere transfer to support flip chip, 2.5D, and 3D packaging using 100 mm to 300mm wafers. The devices supported in Apopka will also be subjected to singulation and die/wafer probe testing.
The Data Scientist is an integral part of the day-to-day operations and routinely works alongside engineering, production and many other organizations here in Apopka, FL. This is a team that comes together to learn, collaborate, and overcome challenges in a fast-paced environment. We are looking for applicants that enjoy working and learning from their peers and are passionate about making a positive difference.
What You’ll Get to Do:
- Provide support to the manufacturing floor by working proactively with cross-functional teams to understand frontline problems and implement cost-saving solutions
- Utilize various Continuous Improvement tools to analyze shop floor practices and processes for opportunities to minimize waste, reduce cost, increase capacity and optimize schedule.
- Work with frontline leadership to assess current state reality and define future state possibilities
- Apply systems thinking in the development of metrics to improve product flow from the release of raw materials through product delivery
- Extract data from an MES (Manufacturing Execution System) and SAP to develop production metrics to drive cost and cycle time reductions.
- Utilizes Data Analytics to analyze existing operational processes and develops metrics and reporting to optimize and improve program & operational performance.
- Leads efforts as Digital Transformation Champion to align Apopka goals with sector and enterprise strategies, including AI adoption
- Creates new metrics and data visualizations to monitor shop floor performance.
- Analyzes lead times, queue times, work-in-process, cycle times, and throughput to meet customer demand most effectively and efficiently.
- Builds scalable and sustainable models to optimize product flow, while incorporating cost, schedule, and resource constraints.
- Develops optimized scheduling tools and aligns SAP/MRP systems with an executable plan given various capacity constraints.
- Turn data into insight with appealing, interactive, and responsive dashboards.
- Assess the effectiveness and accuracy of data sources and data gathering techniques.
- Create and maintain data pipelines to operationalize data.
- Generate metrics and capacity reports.
- Translating business questions and identifying and implementing appropriate modeling or analysis techniques
- Taking projects from initial concept through deployment
- Creating data visualizations using common tools (Python or R libraries, Power BI, Tableau, etc.)
- Utilizing interpersonal and communication skills to present complex models or analyses to business partners
- Collaborating with stakeholders, teammates, and business leaders
- Experience with the Microsoft Office suite.
Basic Qualifications Data Scientist:
- Bachelors in a STEM-related field with 2 years of experience; Master’s with 0 years of experience.
- Experience with Tableau development or similar data application development.
- Experience in creating interactive dashboards
- Experience with merging large datasets from multiple sources
- Experience with building/presenting different metrics and reports.
- Experience with SQL (structured query language) and relational databases.
- The ability to obtain/maintain an active DoD Secret Clearance.
- US Citizenship
Preferred Qualifications Data Scientist:
- Experience in utilizing data from a Manufacturing Execution Systems (MES)
- Experience with SAP and generating dashboards from reports.
- Experience utilizing MRP or ERP systems.
- Experience with software development and deployment
- Experience with developing and deploying applications.
- Experience managing databases, data structures, and data governance.
- Experience with a graphic design background, creating user interfaces, and user-focused dashboards.
- Experience with time series analysis and sequence modeling.
- Experience with implementing Semiconductor SECSGEM capabilities in a production fab
What We Can Offer You:
Northrop Grumman provides a comprehensive benefits package and a work environment which encourages your growth and supports the mutual success of our people and our company. Northrop Grumman benefits give you the flexibility and control to choose the benefits that make the most sense for you and your family.
Your benefits will include the following: Health Plan, Savings Plan, Paid Time Off, and Additional Benefits, including Education Assistance, Training and Development, 9/80 Work Schedule (where available), and much more!
#MPR
Primary Level Salary Range: $87,200.00 - $130,800.00 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 $87K-$130K range is in the lower quartile for Data Scientist roles in our dataset (median: $167K across 150 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 8,943 AI roles we're tracking, Data Scientist positions make up 4% 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 $190,000 based on 1,406 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($109K) sits 43% below the category median. Disclosed range: $87K to $130K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
Northrop Grumman AI Hiring
Northrop Grumman has 13 open AI roles right now. They're hiring across Research Scientist, AI Software Engineer, AI/ML Engineer, Data Scientist. Positions span WV, US, Chandler, AZ, US, Remote, US. Compensation range: $123K - $321K.
Location Context
Across all AI roles, 6% (521 positions) offer remote work, while 8,351 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,416 roles, $263,811 median); Los Angeles (1,340 roles, $210,000 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 $253,100 median, while Prompt Engineer roles sit at $141,440. 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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