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About This Role
##### About Peraton
Peraton is a next\-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world’s leading mission capability integrator and transformative enterprise IT provider, we deliver trusted, highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land, sea, space, air, and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day, our employees solve the most daunting challenges that our customers face. Visit peraton.com to learn how we’re keeping people around the world safe and secure.
##### About The Role
Peraton is seeking an experienced Data Scientist / Project Manager to lead a high\-performing team of engineers, data scientists, and analysts in direct support of U.S. Army Cyber Command's (ARCYBER) Data Management and Analytics Directorate (DMA). This is a dual\-hat leadership role requiring both deep technical expertise in data science and the program management acumen to deliver results on a complex, multi\-functional task order. Location: Fort Gordon, GA.
You will serve as the technical and operational lead for the DMA support team, driving the acquisition, curation, analysis, and visualization of data that enables Army and Joint commanders to make informed, data\-driven decisions. Your team's work directly supports ARCYBER's mission to achieve analytic superiority and information advantage across the DoWIN\-A enterprise.
This role is ideal for a technically grounded leader who thrives at the intersection of data engineering, advanced analytics, and mission\-focused program execution in a classified DoW environment.
Key Responsibilities:
Technical Leadership
- Lead a team of engineers, data scientists, and analysts in the design, development, and delivery of data products and analytic capabilities in support of ARCYBER operations.
- Build, maintain, and optimize Python scripts and packages used by data analysts across the DMA team, establishing reusable frameworks and coding standards.
- Curate and develop a solid data foundation — both structured and unstructured — in close coordination with the government client, ensuring data is Visible, Accessible, Understandable, Linked, Trustworthy, Interoperable, and Secure (VAULTIS).
- Process modeling data and perform robust analytics to support operational and strategic decision\-making for Army and Joint organizational elements.
- Apply online experimentation, Machine Learning (ML), natural language processing (NLP), and dynamic network analysis to develop personalized, mission\-relevant data products.
- Oversee integration of analytics and visualizations into the Army's Big Data Platform (BDP), Gabriel Nimbus, and related platforms (AWS GovCloud, Microsoft Azure, Google Cloud).
- Provide architectural oversight to ensure DMA data products, pipelines, and cloud environments align with DoD and Army reference architectures and enterprise data standards.
Program Management
- Serve as the accountable program manager for the successful technical, schedule, and cost performance of the DMA support team in accordance with Task Order (TO) contract requirements and Peraton company policies.
- Monitor and manage all phases of the project budget; coordinate with the government client on TDP funding, provide financial forecasts, and ensure cost performance remains within approved parameters.
- Maintain program documentation, status reporting, and deliverable compliance in accordance with contract requirements — including Monthly Status Reports (NLT 10 days after month start), In\-Progress Reviews (IPRs), and CSSP certification artifacts.
- Identify and mitigate program risks; escalate issues to the Program Director with recommended courses of action.
- Coordinate with ARCYBER G3, DMA leadership, and Peraton leadership to align team priorities with mission requirements and contract objectives.
Business Development
- Identify and pursue follow\-on business opportunities associated with the DMA portfolio and ARCYBER cyberspace operations support.
- Lead or contribute to major proposals, white papers, and capability briefings in support of new business development efforts.
- Represent Peraton's DMA capabilities to government stakeholders, building relationships that support long\-term program growth.
People Leadership
- Supervise, mentor, and develop a team of professional and technical personnel across the DMA functional areas: Integration \& Data (ID2\), Data Governance, Data Analysis, Knowledge Management, G33 Operations Support, and Enterprise Architecture.
- Conduct performance evaluations, support career development planning, and maintain aggressive efforts to achieve individual and team objectives.
- Foster a culture of technical excellence, accountability, and continuous improvement aligned with Peraton's values.
##### Qualifications
Required Qualifications:
- Minimum of 16 years with BS/BA; Minimum of 14 years with MS/MA; Minimum of 10 years with Ph.D.
- Proficiency in Python for data engineering, analytics, and automation (scripting, packages, Jupyter environments)
- Hands\-on experience with Machine Learning frameworks and NLP techniques
- Experience with cloud platforms — AWS GovCloud, Microsoft Azure, and/or Google Cloud
- Familiarity with big data platforms and tools (e.g., Spark, Kafka, Hadoop, or equivalent)
- Experience with data visualization tools (Power BI, Tableau, or equivalent)
- Demonstrated experience managing cost, schedule, and technical performance on DoD task orders
- Experience with Agile/Scrum methodologies and tools (e.g., Jira)
- Familiarity with DoD data governance frameworks, RMF, and CSSP requirements
- Active TS clearance with ability to obtain/maintain SCI, Polygraph and MEAD
- U.S. Citizenship required.
Preferred Qualifications:
- Bachelor's degree in Data Science, Computer Science, Mathematics, Statistics, Engineering, or a related technical field; a Master's degree in a relevant technical or analytical field is highly desirable
- 10\+ years of relevant experience, including at least 3 years in a technical program or project management role on DoD contracts
- Experience supporting ARCYBER, USCYBERCOM, or Army cyber mission partners
- Familiarity with Gabriel Nimbus (GN), IONIC, ALEX, or the Army Big Data Platform (BDP)
- Knowledge of MITRE ATT\&CK framework and its application to defensive cyber analyticss
- Experience with JCWA platforms (Unified Platform, JCC2, JCHK, PCTE)
- PMP, DAU Program Management, or equivalent certification
- Experience with DoD data strategy frameworks (VAULTIS, DoD Data Strategy 2020\)
- Prior experience leading proposals and winning follow\-on business in the DoD cyber domain
##### Details
Target Salary Range: $176,000 \- $282,000\. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual’s experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.
Benefits Statement: Peraton offers eligible employees a variety of benefits including medical, dental, vision, life, health savings account, short/long term disability, EAP, parental leave, 401(k), paid time off (PTO) for vacation, and company paid holidays. A full listing of available benefits can be viewed at https://www.careers.peraton.com/benefits.
Application Statements: The application period for the job is estimated to be 30 days from the job posting date. However, this timeline may be shortened or extended depending on business needs and the availability of qualified candidates. By applying to this job, you are expressing interest in the role and the Company. During the review of your application, you may be required to participate in an on\-camera interview, as well as participate in a process to verify your identity.
EEO: Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law.
Salary Context
This $176K-$282K range is above the 75th percentile 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 Peraton, 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 ($229K) sits 19% above the category median. Disclosed range: $176K to $282K.
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.
Peraton AI Hiring
Peraton has 3 open AI roles right now. They're hiring across Research Engineer, Data Scientist. Positions span Bedford, NH, US, Laurel, MD, US, Fort Gordon, GA, US. Compensation range: $234K - $282K.
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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