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About This Role
Job ID
329256
Job Title: Data Scientist, SME
Job Category: Science
Time Type: Full time
Minimum Clearance Required to Start: TS/SCI
Employee Type: Regular
Percentage of Travel Required: Up to 10%
Type of Travel: Local
\* \* \*The Opportunity:
CACI is currently seeking a Data Scientist II in support of a program whose initiative is aimed at combating evolving and emerging threats, supporting related exploitation and replication activities, and advancing operational rehearsal, exercise, wargaming, and counter system development....
Opportunity
As the Data Scientist SME, you will lead the development of novel AI solutions—from generative models to reinforcement learning agents—to solve complex problems in high\-fidelity simulation, operational planning, and human\-machine interfacing .
This position offers the opportunity to work at the forefront of defense technology, applying cutting\-edge data science and AI/ML methodologies to support warfighter readiness and mission success in the INDOPACOM region and beyond.
Responsibilities:
- Lead AI/ML Innovation: Direct the architecture and development of advanced AI/ML solutions including deep learning, reinforcement learning, natural language processing (NLP), and computer vision applications for defense programs
- Pioneer Novel Solutions: Design and implement generative models and reinforcement learning agents to address complex challenges in high\-fidelity simulation environments, operational planning, and human\-machine interfacing
- Support Critical DOD Programs: Provide strategic technical guidance on data science initiatives that directly impact military readiness, training, and operational effectiveness
- Advanced Data Analysis: Transform complex, multi\-source data into actionable intelligence through sophisticated analytical models and data pipelines
- AI\-Simulation Integration: Design and develop data\-driven solutions for Modeling \& Simulation (M\&S) and AI systems, including creating and refining generative AI analysis workflows
- Infrastructure Support: Provide technical expertise in modeling and simulation equipment, systems engineering, and cybersecurity operations across government offices, laboratories, and test locations
- Collaborative Leadership: Work across multidisciplinary teams, including systems engineers, operations research analysts, and program managers to deliver integrated solutions
- Strategic Planning: Develop technical roadmaps and strategic plans for AI/ML integration into Live, Virtual, and Constructive (LVC) simulation architectures
- Knowledge Transfer: Mentor junior team members and provide training on advanced data science methodologies and AI/ML best practices
Qualifications:
*Required:*
- Bachelor's degree in Computer Science, Data Science, Statistics, or related field
- Minimum 10 years of demonstrated experience leading the application of advanced data science and AI/ML in complex technical environments or 15\+ years relevant experience in lieu of degree
- Expert\-level proficiency in AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit\-learn)
- Advanced programming skills in Python, R, or similar languages
- Experience with big data platforms and cloud computing architectures (AWS, Azure, Google Cloud)
- Knowledge of data engineering, ETL processes, and database management
- Familiarity with Model\-Based Systems Engineering (MBSE) tools and methodologies
- Active TS/SCI Clearance
*Desired:*
- Master's degree or Ph.D. in a related field highly valued
- 15\+ years of relevant experience in data science and AI/ML
- Experience with DOD or Department of the Army (DOW) programs, particularly INDOPACOM operations
- Hands\-on experience with Joint Simulation Environments and federated/non\-federated LVC M\&S tools (e.g., JTLS\-GO, OneSAF, JSAF)
- Knowledge of cybersecurity principles and Zero Trust architectures
- Experience with Cross Domain Solutions (CDS) for secure data exchange
- Familiarity with Digital Engineering (DE) methodologies and tools
- Experience supporting large\-scale Command Post Exercises (CPXs) and Field Training Exercises (FTXs)
- Project Management Professional (PMP) or similar certification
*
What You Can Expect:
A culture of integrity.
At CACI, we place character and innovation at the center of everything we do. As a valued team member, you’ll be part of a high\-performing group dedicated to our customer’s missions and driven by a higher purpose – to ensure the safety of our nation.
An environment of trust.
CACI values the unique contributions that every employee brings to our company and our customers \- every day. You’ll have the autonomy to take the time you need through a unique flexible time off benefit and have access to robust learning resources to make your ambitions a reality.
A focus on continuous growth.
Together, we will advance our nation's most critical missions, build on our lengthy track record of business success, and find opportunities to break new ground — in your career and in our legacy.
Pay Range:
There are a host of factors that can influence final salary including, but not limited to, geographic location, Federal Government contract labor categories and contract wage rates, relevant prior work experience, specific skills and competencies, education, and certifications. Our employees value the flexibility at CACI that allows them to balance quality work and their personal lives. We offer competitive compensation, benefits and learning and development opportunities. Our broad and competitive mix of benefits options is designed to support and protect employees and their families. At CACI, you will receive comprehensive benefits such as; healthcare, wellness, financial, retirement, family support, continuing education, and time off benefits.
Since this position can be worked in more than one location, the range shown is the national average for the position.
The proposed salary range for this position is:
$98,500\-$206,800*CACI is* *an Equal Opportunity Employer.* *All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, age, national origin, disability, status as a protected veteran, or any* *other protected characteristic.*
Salary Context
This $98K-$206K range is below the median 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 CACI International, 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. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($152K) sits 21% below the category median. Disclosed range: $98K to $206K.
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.
CACI International AI Hiring
CACI International has 6 open AI roles right now. They're hiring across Data Scientist, Research Engineer, AI/ML Engineer, Prompt Engineer. Positions span Camp Smith, HI, US, Florham Park, NJ, US, Remote, US. Compensation range: $133K - $290K.
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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