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About This Role
Innovative Technologies Corporation (ITC) is seeking a Senior Data Scientist to support a proposal we are bidding on. This position is located in the National Capital Region (Pentagon, onsite). We estimate the award will be made in late August to September 2026 with a PoP starting 1 Nov 2026\.
The Senior Data Scientist provides advanced analytical expertise supporting the Air Force Mission Assurance Program. This position develops predictive analytics, statistical models, data visualizations, and decision\-support products that help senior Air Force leaders understand mission risk, critical asset dependencies, and operational readiness using enterprise data platforms and advanced analytical techniques.
Required Clearance Level
- Current, active, and valid Top Secret security clearance.
Required Qualifications
- Master’s degree in Data Science, Computer Science, Mathematics, Statistics, Engineering, Operations Research, or a closely related technical discipline.
- Minimum 10 years of professional analytical or data science experience.
- Demonstrated experience applying statistical analysis, predictive analytics, machine learning, or advanced analytical methodologies.
- Experience developing enterprise data products, dashboards, reports, and executive decision\-support products.
- Experience using enterprise data platforms to collect, organize, analyze, and visualize large data sets.
- Ability to obtain the Palantir Foundry Application Developer Certification within 90 calendar days after contract award and maintain certification throughout the contract.
- Expertise in oral and written English communications skills.
- Advanced skills in the Microsoft Office environment is essential (Word, PowerPoint, Excel, Teams, SharePoint).
Desired Qualifications
- Experience supporting Air Force or Department of Defense organizations.
- Experience supporting Mission Assurance, Critical Asset Risk Management, or operational risk analysis.
- Experience with Palantir Foundry.
- Experience with Python, R, SQL, Power BI, Tableau, or comparable analytical tools.
- Experience presenting analytical findings to senior Government leadership.
- Experience integrating multiple enterprise data sources into a common analytical environment.
Key Responsibilities
- Develop advanced analytical models supporting Mission Assurance decision making.
- Analyze mission, assessment, operational, and risk data.
- Develop dashboards, reports, predictive models, and decision\-support products.
- Support Government implementation of enterprise analytical platforms including Palantir Foundry.
- Identify trends, vulnerabilities, dependencies, and operational risk indicators.
- Present analytical findings and recommendations to Government leadership.
- Support continuous improvement of analytical methodologies and enterprise data products.
- Ensure compliance with Government security, data management, and cybersecurity requirements.
About ITC
Innovative Technologies Corporation (ITC) offers challenging but rewarding opportunities for those who want to provide a great experience for the customer and strive to reach their professional goals. As a member of ITC, you will be working alongside people providing innovative solutions to our government customers. Our success is built on integrity, loyalty, and trust. ITC has a commitment to provide the right people for the job, right when they are needed.
Compensation \& Benefits
The Salary for this contingent hire position is $150,000 to $175,000 based on experience and includes medical/dental/vision benefits, 10 days PTO and 7 days sick time; other benefits available.
This is a contingent position for a proposal we are bidding on (published July 21, 2026\). Additional information provided during interview.
Key Words
Data Scientist, Senior Data Scientist, Data Science Consultant, Machine Learning, Predictive Analytics, Statistical Analysis, Palantir Foundry, Data Visualization, Power BI, Tableau, Python, R, SQL, Mission Assurance, Air Force, Department of Defense, Pentagon, TS Clearance, TS/SCI, NCR, Enterprise Analytics
Pay: $150,000\.00 \- $175,000\.00 per year
Benefits:
- 401(k)
- 401(k) matching
- Dental insurance
- Employee assistance program
- Employee discount
- Flexible spending account
- Health insurance
- Health savings account
- Life insurance
- Paid time off
- Professional development assistance
- Referral program
- Tuition reimbursement
- Vision insurance
People with a criminal record are encouraged to apply
Application Question(s):
- ITC may request a Letter of Intent (LOI) for this proposal position. If offered this role upon contract award, what annual salary range would you be willing to commit to accepting? Please provide your acceptable salary range for this position
Education:
- Master's (Required)
Experience:
- analytical or data science: 10 years (Required)
Security clearance:
- Top Secret (Required)
Ability to Commute:
- Pentagon, DC 20301 (Required)
Work Location: In person
Salary Context
This $150K-$175K range is above 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 Innovative Technologies Corporation, 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. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($162K) sits 16% below the category median. Disclosed range: $150K to $175K.
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.
Innovative Technologies Corporation AI Hiring
Innovative Technologies Corporation has 1 open AI role right now. They're hiring across Data Scientist. Based in Pentagon, DC, US. Compensation range: $175K - $175K.
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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