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About This Role
Overview: JOB TITLE: Software/ML Engineer – Junior to Senior LevelJOB TITLE: Data Scientist – Junior to Senior LevelGOVERNMENT AGENCY: Microsoft/NGA – National Geospatial-Intelligence AgencyPOSITION INFORMATION: Full-Time Position; Government contractor supporting Microsoft's Spectre team and the NGAEXPERIENCE LEVEL: Junior, Mid, or Senior Level – all levels encouraged to applyLOCATION: Hybrid (2 days onsite at SCIF, 3 days remote) – Springfield, VA (NGA, preferred); Reston, VA; or Redmond, WABENEFITS: Health, Dental and Vision, 401(k), Flexible Spending Account (FSA), 11 Paid Federal Holidays, PTO, education reimbursement
ITC Federal, LLC (ITC), headquartered in Fairfax, VA, delivers automation, AI, data, and digital modernization solutions that strengthen national security and solve complex government mission challenges. With its recent acquisition of ITC Digital Solutions (formerly Capgemini Government Solutions), ITC combines a long-standing national security delivery record with modern cloud, data, and enterprise platform expertise.
ITC is seeking a motivated Data Scientist to support Microsoft's Spectre team, which is advancing the state of the art in Geospatial AI. In collaboration with Microsoft Planetary Computer, Spectre develops foundation models for aerial object detection, tracking, and map generation, and an end-to-end AI platform that turns petabytes of data into accurate geospatial insights for mission customers. The team moves fast from ideas to experimentation to product development. All Experience Levels Encouraged to Apply: This position can be filled at the junior, mid, or senior level. We are most focused on skills and fit with the program, and candidates at all levels are encouraged to apply.
Responsibilities:
RESPONSIBILITIES:* AI & Computer Vision Development
- + Apply the latest AI, Computer Vision, and Machine Learning algorithms to build customer-centric solutions. + Modify and advance state-of-the-art approaches in Computer Vision to deliver best-in-class solutions to our customers.
- Performance Optimization
- + Optimize the run-time performance of the latest Computer Vision and Machine Learning algorithms to meet customer requirements on various hardware platforms.
- Collaboration & Culture
- + Partner with industry-leading Engineers, Data Scientists, Designers, and Program Managers to deliver solid technical designs. + Embody our Culture and Values.
Qualifications:
REQUIRED:* Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field, required.
- Proven experience in data science, software development, data modeling, or data engineering, OR equivalent experience. Candidates with additional experience will be considered at the mid or senior level.
- Data modeling experience required.
PREFERRED:* Experience with C++/Python and debugging ability across technology stacks.
- Experience in Deep Learning using frameworks such as PyTorch and TensorFlow.
- Experience shipping Computer Vision or Machine Learning based runtimes.
- Practical experience working with geospatial workflows or datasets.
SECURITY CLEARANCE REQUIREMENTS:* Must have an active Top Secret (TS) security clearance; TS/SCI preferred but not required.
- U.S. Citizenship is required due to the nature of this government contract.
WORK LOCATION:* Hybrid role: 2 days onsite at a SCIF and 3 days remote. SCIF work location options:
- Preferred location: National Geospatial-Intelligence Agency (NGA), 7500 GEOINT Drive, Springfield, VA 22150
- Alternative secure space (back-up option): Microsoft Office, 12012 Sunset Hills Rd., Suite 100, Reston, VA 20190
- Alternative secure space (back-up option): Microsoft Corporation, One Microsoft Way, Redmond, WA 98052
WORK ENVIRONMENT AND PHYSICAL DEMANDS: Candidate must be able to function in general office environment.
ITC Federal is an equal opportunity employer and will not discriminate against any application for employment on the basis of age, race, color, gender, national origin, religion, creed, disability, veteran status, marital status, sexual orientation, genetic information, military status, disability, or sex including pregnancy and childbirth or related medical condition or on any other basis prohibited by law.
Salary Context
This $120K-$160K range is below the median for Data Scientist roles in our dataset (median: $162K across 195 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 11,520 AI roles we're tracking, Data Scientist positions make up 4% of the market. At ITC Federal, 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 1,564 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($140K) sits 26% below the category median. Disclosed range: $120K to $160K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
ITC Federal AI Hiring
ITC Federal has 1 open AI role right now. They're hiring across Data Scientist. Based in Redmond, WA, US. Compensation range: $160K - $160K.
Location Context
Across all AI roles, 6% (708 positions) offer remote work, while 10,737 require on-site attendance. Top AI hiring metros: New York (3,257 roles, $221,000 median); San Francisco (2,766 roles, $260,550 median); Los Angeles (1,580 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 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 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 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). 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 (140) are outnumbered by mid-level (5,630) and senior (4,176) 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 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 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 $213,480. Top-quartile roles start at $264,000, and the 90th percentile reaches $318,400. 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 $266,050 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 (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 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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