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About This Role
Minimum Clearance Required: TS/SCI Responsibilities:
I2X Technologies is a reputable technology services company to the Federal Government. Whether the focus is on space exploration, national security, cyber security, or cutting\-edge engineering applications, I2X is ready to offer you the chance to make a real\-world impact in your field and for your country. We provide long\-term growth and development. Headquartered in Colorado, I2X is engaged in programs across the country and in more than 20 states. Our programs support multiple Federal agencies, the Department of Defense and often focused on the space initiatives of our government customers. Functional Responsibilities:I2X Technologies is seeking a Data Scientist Job Duties:
Our team needs a full\-time AI/ML Engineer. In this role, you will be responsible for software development and design for Artificial Intelligence and Machine Learning systems, model creation, data science / analytics, and interaction with systems engineers, architects, scrum masters, product owners, and end users to deliver AI / ML mission capabilities for U.S. Strategic Command. This position will also include acting as an AI / ML resource for the usage of AI / ML automation throughout the engineering lifecycle.
Must be a US Citizen. This position will require a TS/SCI security clearance.
Qualifications:
Experience Requirements: Basic Qualifications:
- BS in Computer Science, Software Engineering, Computer Engineering, Data Science or equivalent STEM field
- Must be a US Citizen; this position will require a government security clearance. This position is located at a facility that requires special access
- Demonstrated proficiency in developing algorithms and performing analytical problem\-solving using Python
- Familiarity integrating AI/ML Solutions into operational mission systems
Desired Skills:
- U.S. Strategic Command mission insight (Intel, Planning, or C2\)
- MLOps experience
- Experience with AI / ML usage in engineering lifecycles (generative coding)
- Experience evaluating and testing AI / ML solutions
- Engineering experience with AFNWC SMPES, MPAS, NPES Systems
Essential Requirements:
US Citizenship is required.
This position will require a TS/SCI security clearance.
In compliance with Colorado’s Equal Pay for Equal Work Act, the annual base salary range for this position is listed . Please note that the salary information is a general guideline only. I2X Technologies considers factors such as (but not limited to) scope and responsibilities of the position, candidate’s work experience, education/training, key skills, internal peer equity, as well as, market and business considerations when extending an offer. Physical Demands:
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job with or without reasonable accommodation.
While performing the duties of this job, the employee will regularly sit, walk, stand and climb stairs and steps. May require walking long distance from parking to work station. Occasionally, movement that requires twisting at the neck and/or trunk more than the average person, squatting/ stooping/kneeling, reaching above the head, and forward motion will be required. The employee will continuously be required to repeat the same hand, arm, or finger motion many times. Manual and finger dexterity are essential to this position. Specific vision abilities required by this job include close, distance, depth perception and telling differences among colors. The employee must be able to communicate through speech with clients and public. Hearing requirements include conversation in both quiet and noisy environments. Lifting may require floor to waist, waist to shoulder, or shoulder to overhead movement of up to 20 pounds. This position demands tolerance for various levels of mental stress.
I2X Technologies is an Engineering and Information Technology Company focused on providing Services to the Federal and State Government. I2X offers a competitive compensation program and comprehensive benefits package to our employees.
Salary Context
This $140K-$160K range is below the median for Data Scientist roles in our dataset (median: $160K across 258 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 4,317 AI roles we're tracking, Data Scientist positions make up 8% of the market. At Isys Technologies, 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 789 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($150K) sits 22% below the category median. Disclosed range: $140K to $160K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Isys Technologies AI Hiring
Isys Technologies has 1 open AI role right now. They're hiring across Data Scientist. Based in Bellevue, NE, US. Compensation range: $160K - $160K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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