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AI/Data Solutions Engineer TS/SCI (FSP)

Pay
Pay not listedSimilar roles state $118K–$194K
Work setting
Not stated
Employment
Not stated

Before you apply

Work authorization
US citizens only*** Candidate is required to have US Citizenship for this role without exception

What you’ll work on

Full posting
  • Work directly with raw, incomplete data to structure and process it

  • Build and support data pipelines for repeatable processing

  • Develop models and analytical methods to find patterns and signals

  • Integrate internal and external models into working systems and adjust them as data changes

  • Mentor junior engineers and scientists through code review and working sessions

From the employer’s posting
Work directly with raw and incomplete data, determining how to structure, process, and use it effectively.
Build and support data pipelines that enable consistent, repeatable processing across datasets.
Develop and apply models and analytical methods to identify meaningful patterns, behaviors, and signals.
Integrate internal and external models into working systems and adjust them as conditions or data changes.
Provide direct feedback through code review and working sessions.
Education & alternatives
Clearance & Logistics: US Citizenship is required. Candidates must possess an active Top Secret/SCI (TS/SCI) clearance with a Full Scope Polygraph on Day 1 and be able to work onsite in the Washington, DC Metro Area (Chantilly, VA). Work is performed in a secure environment with limited remote flexibility. Education & Experience: Bachelor's degree in Computer Science, Engineering, Mathematics, or related technical field, or equivalent practical experience, with 5 or more years of experience in data science, machine learning, or applied data roles, with a track record of applying skills to real-world problems. Programming & Data Fundamentals: Strong proficiency in Python and working knowledge of SQL. Demonstrated ability to work directly with raw data to explore, transform, and analyze datasets without relying on pre-built tooling.
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Posting record

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Actively hiringFirst seen by us 8 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 1, 20268 days ago
Recorded sightings
9
Last seen by us
Nov 9, 2026
Employer says posted
Jun 16, 2026

We found this posting on the National Labor Exchange. These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$118K–$194K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 3,819 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 8

Similar jobs usually come down between day 7 and day 57.

From 10,789 similar postings that came down. Coming down is not always a hire.

IBM is hiring

215 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

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  • Python
  • SQL
Where the posting names them
Education & Experience: Bachelor's degree in Computer Science, Engineering, Mathematics, or related technical field, or equivalent practical experience, with 5 or more years of experience in data science, machine learning, or applied data roles, with a track record of applying skills to real-world problems. Programming & Data Fundamentals: Strong proficiency in Python and working knowledge of SQL. Demonstrated ability to work directly with raw data to explore, transform, and analyze datasets without relying on pre-built tooling. Data Processing & Systems: Experience contributing to data pipelines and processing workflows, including ingestion and transformation, and handling of large or complex datasets.

Your next step

Complete your application on www.ibm.com. The employer’s form will show what is required.

Already applied? Track this application

Has IBM posted this job before?

Yes. We’ve followed 11 other AI/Data Solutions Engineer TS/SCI (FSP) jobs there since November 2026. All 11 are still up.

  1. RestonStill up after 9 days, first seen Nov 1
  2. Annapolis JunctionStill up after 9 days, first seen Nov 1
  3. ChantillyStill up after 9 days, first seen Nov 1
  4. BethesdaStill up after 9 days, first seen Nov 1
  5. FrederickStill up after 9 days, first seen Nov 1
  6. WashingtonStill up after 9 days, first seen Nov 1
  7. AlexandriaStill up after 9 days, first seen Nov 1
  8. CatonsvilleStill up after 9 days, first seen Nov 1
  9. This jobUp 9 days so far, first seen Nov 1

Large employers often post one title for several teams, so these can be separate openings.

About IBM

People
About 216,044 in 2024.Benefit plan filings (Form 5500)
Company
Listed as IBM.
H-1B visas
591 approved for new hires in fiscal 2025.US Citizenship and Immigration Services

Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 5% over the last 6 weeks compared with the 6 before.

Weekly new Data Scientist postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 1,408, the most 2,964, and the latest week had 2,139.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

**Introduction** At IBM, the work is about building things that matter. You will be working on real problems in a mission environment where the output of your work is used, not just presented. We are looking for a hands-on data and engineering professional who can take messy, incomplete information and turn it into something useful and clear. This role is about going from raw data to real understanding and doing it in a way that people can act on immediately, with confidence. You will work across the full lifecycle of work. That includes getting data, shaping it, building models where needed, and delivering outputs that help people make decisions. This is not a role where someone hands you a clean dataset or defined problem. You will also work closely with junior team members. Part of your responsibility is helping them grow into strong, independent contributors by working alongside them, giving them ownership, and holding a high bar for quality. **Your role and responsibilities** *** Candidate is required to have US Citizenship for this role without exception. Candidates must also have an approved, active US Government Top Secret/SCI security clearance with Full Scope Polygraph and be able to sit onsite in the Washington DC Metro area. *** The Data Solutions Engineer is a hands-on technologist and problem solver who works across data, systems, and analysis to deliver outcomes that are usable in real mission conditions. This role is responsible for contributing to solutions that take raw, fragmented data and turn it into something clear, reliable, and actionable. The focus is on building work that holds up in operational use, not just in controlled environments. You will contribute across the workflow, from how data is handled through how it is used, making practical decisions that balance technical quality with mission needs. You will: * Work directly with raw and incomplete data, determining how to structure, process, and use it effectively. * Develop and apply models and analytical methods to identify meaningful patterns, behaviors, and signals. * Build and support data pipelines that enable consistent, repeatable processing across datasets. * Integrate internal and external models into working systems and adjust them as conditions or data changes. * Operate effectively in secure and constrained environments where tradeoffs are required. Team Development and Collaboration: * Work directly with junior data engineers and data scientists as part of day-to-day delivery. * Help them take ownership of defined components and hold them accountable for outcomes. * Provide direct feedback through code review and working sessions. * Break down complex problems so others can contribute and build confidence. * Support a team environment where responsibility is shared and expectations are clear. **Required technical and professional expertise** Clearance & Logistics: US Citizenship is required. Candidates must possess an active Top Secret/SCI (TS/SCI) clearance with a Full Scope Polygraph on Day 1 and be able to work onsite in the Washington, DC Metro Area (Chantilly, VA). Work is performed in a secure environment with limited remote flexibility. Education & Experience: Bachelor's degree in Computer Science, Engineering, Mathematics, or related technical field, or equivalent practical experience, with 5 or more years of experience in data science, machine learning, or applied data roles, with a track record of applying skills to real-world problems. Programming & Data Fundamentals: Strong proficiency in Python and working knowledge of SQL. Demonstrated ability to work directly with raw data to explore, transform, and analyze datasets without relying on pre-built tooling. Data Processing & Systems: Experience contributing to data pipelines and processing workflows, including ingestion and transformation, and handling of large or complex datasets. Applied Modeling and Analysis: Experience building and applying models or analytical approaches in real-world settings, with an understanding of how to adapt to changing data and requirements. Data Types & Complexity: Experience working with multiple forms of data such as text, imagery, video, or sensor data, and the ability to extract meaningful patterns from incomplete or noisy inputs. Operational & Secure Environment: Experience working in distributed, standalone, or secure environments, adapting approaches to system and security constraints. Model Use & Lifecycle Awareness: Experience putting models or analytical outputs into use and monitoring performance over time, including recognizing when adjustments are needed. Ways of Working: Ability to operate effectively in team-based environments with shared ownership and accountability. Demonstrates sound judgement when working through ambiguous or evolving problems and contributes to both delivery and team capability. **Preferred technical and professional experience** Candidates may come from different technical backgrounds but should demonstrate exposure across data, systems, and analysis. Mission & Domain Experience: experience supporting or delivering solutions within the IC or DoD, particularly in secure, mission-driven, or air-gapped environments. Data & Analytical Techniques: experience working with imagery data or applying computer vision techniques. Familiarity with newer modeling approaches when applied in practical, real-word settings. Data Processing & Systems: experience working with real-time or streaming data or building workflows that support continuous data processing and analysis. Strong preference for candidates who default to code-driven analysis rather than relying on GUI-based tools. Cloud & Infrastructure Exposure: exposure to clou or hybrid environments within secure constraints, with an understanding of how infrastructure impacts data and system design. Integration & Tooling: experience with APIs, system integration, or container-based workflows, including adapting tools and components to fit within larger systems. Team Development & Growth: demonstrated ability to support and develop junior team members through hands-on collaboration, guidance, and shared delivery of work. IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.
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Pay

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Location & working pattern

Mclean, VA

**Required technical and professional expertise** Clearance & Logistics: US Citizenship is required. Candidates must possess an active Top Secret/SCI (TS/SCI) clearance with a Full Scope Polygraph on Day 1 and be able to work onsite in the Washington, DC Metro Area (Chantilly, VA). Work is performed in a secure environment with limited remote flexibility. Education & Experience: Bachelor's degree in Computer Science, Engineering, Mathematics, or related technical field, or equivalent practical experience, with 5 or more years of experience in data science, machine learning, or applied data roles, with a track record of applying skills to real-world problems.
More source context
Data Processing & Systems: experience working with real-time or streaming data or building workflows that support continuous data processing and analysis. Strong preference for candidates who default to code-driven analysis rather than relying on GUI-based tools. Cloud & Infrastructure Exposure: exposure to clou or hybrid environments within secure constraints, with an understanding of how infrastructure impacts data and system design. Integration & Tooling: experience with APIs, system integration, or container-based workflows, including adapting tools and components to fit within larger systems.
Work authorization
**Your role and responsibilities** *** Candidate is required to have US Citizenship for this role without exception. Candidates must also have an approved, active US Government Top Secret/SCI security clearance with Full Scope Polygraph and be able to sit onsite in the Washington DC Metro area. *** The Data Solutions Engineer is a hands-on technologist and problem solver who works across data, systems, and analysis to deliver outcomes that are usable in real mission conditions.
More source context
**Required technical and professional expertise** Clearance & Logistics: US Citizenship is required. Candidates must possess an active Top Secret/SCI (TS/SCI) clearance with a Full Scope Polygraph on Day 1 and be able to work onsite in the Washington, DC Metro Area (Chantilly, VA). Work is performed in a secure environment with limited remote flexibility. Education & Experience: Bachelor's degree in Computer Science, Engineering, Mathematics, or related technical field, or equivalent practical experience, with 5 or more years of experience in data science, machine learning, or applied data roles, with a track record of applying skills to real-world problems.

More relevant text appears in the full description.

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