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Remote Machine Learning Quant Jobs in Ashburn, VA

System One

Mid-Level Data Scientist

Merrifield, VA · Remote

Hybrid - onsite and remote Responsibilities * Collaborate with senior data scientists and leaders ... Utilize traditional and machine learning techniques and tools to build a variety of models ...

New

GRVTY

Data Scientist, Senior

Chantilly, VA · On-site +1

The core of the work is applying machine learning, statistical analysis, and data mining techniques ... Experience with geospatial data, imagery products, or remote sensing datasets -- familiarity with ...

GRVTY

Imagery Scientist (EO) - Senior

Falls Church, VA · On-site +1

$160K - $190K/yr

... Machine Learning algorithm testing and evaluation. The ideal candidate is an expert imagery ... Remote sensing phenomenology * Image formation processes * Exploitation products and methodologies

GRVTY

Data Scientist, Senior

Chantilly, VA · On-site +1

The core of the work is applying machine learning, statistical analysis, and data mining techniques ... Experience with geospatial data, imagery products, or remote sensing datasets - familiarity with ...

1872 Consulting

Principal Architect

Herndon, VA · On-site +1

Deep knowledge of machine learning processes and scalability solutions. Experience working with remote sensing data, ideally satellite imagery with an understanding of Geospatial software (GDAL ...

1872 Consulting

Principal Architect

Herndon, VA · On-site +1

Deep knowledge of machine learning processes and scalability solutions. Experience working with remote sensing data, ideally satellite imagery with an understanding of Geospatial software (GDAL ...

Booz Allen Hamilton, Inc.

Data Scientist

Arlington, VA · On-site +1

$77K - $176K/yr

... quantitative analyses and visualization of targeted data sources * Knowledge of Machine Learning ... Remote : If this position is listed as remote, there may still be occasions when you are required ...

Booz Allen Hamilton, Inc.

Data Scientist

Chantilly, VA · On-site +1

$62K - $141K/yr

Knowledge of Machine Learning, Artificial Intelligence, or Natural Language Processing * Ability to ... Remote : If this position is listed as remote, there may still be occasions when you are required ...

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Remote Machine Learning Quant information

See Ashburn, VA salary details

$11.2K

$132.6K

$202.5K

How much do remote machine learning quant jobs pay per year?

As of Sep 5, 2026, the average yearly pay for remote machine learning quant in Ashburn, VA is $132,597.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,100.00 and $141,600.00 per year, depending on experience, location, and employer.

What is the difference between Remote Machine Learning Quant vs Remote Data Scientist?

AspectRemote Machine Learning QuantRemote Data Scientist
Required CredentialsAdvanced degrees in quantitative fields, certifications in machine learning or financeDegrees in data science, statistics, or related fields; certifications like CAP or DASCA
Work EnvironmentFinancial firms, hedge funds, or quantitative trading companiesTech companies, research institutions, or consulting firms
Industry UsageFinance, trading, hedge fundsTechnology, healthcare, marketing, finance
Common Search/ComparisonYesNo

Remote Machine Learning Quants focus on developing quantitative models for trading and investment strategies within financial firms, often requiring finance-specific knowledge. Remote Data Scientists work across various industries, applying data analysis and machine learning to solve diverse business problems. While both roles involve machine learning, Quants are more finance-oriented, whereas Data Scientists have broader industry applications.

What are the most commonly searched types of Machine Learning Quant jobs in Ashburn, VA?

The most popular types of Machine Learning Quant jobs in Ashburn, VA are:

What are popular job titles related to Remote Machine Learning Quant jobs in Ashburn, VA?

For Remote Machine Learning Quant jobs in Ashburn, VA, the most frequently searched job titles are:

What job categories do people searching Remote Machine Learning Quant jobs in Ashburn, VA look for?

The top searched job categories for Remote Machine Learning Quant jobs in Ashburn, VA are:

What cities near Ashburn, VA are hiring for Remote Machine Learning Quant jobs?

Cities near Ashburn, VA with the most Remote Machine Learning Quant job openings:

Remote Machine Learning Quant jobs near you
Infographic showing various Remote Machine Learning Quant job openings in Ashburn, VA as of August 2026, with employment types broken down into 45% Full Time, 20% Part Time, and 35% Contract. Highlights an 100% Remote job distribution, with an average salary of $132,597 per year, or $63.7 per hour.

SAR Data/Imagery Scientist (TS/SCI Clearance required)

NorthHill Technology

Falls Church, VA • On-site, Remote

Full-time

Re-posted 22 days ago

Key responsibilities

  • Support the evaluation of emerging sensor capabilities and compare new collection platforms with existing systems.

  • Assess the impact of new sensor data on data architectures, including metadata, file formats, schemas, APIs, and ETL processes.

  • Develop preprocessing and standardization workflows to prepare imagery for labeling, analytics, and AI/ML model testing.

Job description

NorthHill Technology Resources has a need for a SAR Data Scientist/Imagery Scientist to join a Federal Program in Falls Church, VA.  This is a direct-hire opportunity with our client, a highly respected Federal Integrator.  A current TS/SCI Clearance is required. 

We are seeking an experienced SAR Data Scientist/Imagery Scientist to join a high-performing team supporting advanced AI and machine learning initiatives for complex national security and intelligence missions.

This program focuses on evaluating AI models against Government datasets to assess their performance, resilience, and robustness across a broad spectrum of adversarial scenarios. The effort also includes testing and validating autonomous algorithms designed to support operational decision-making in dynamic mission environments.

As a SAR Exploitation/Imagery Scientist, you will provide subject matter expertise in Synthetic Aperture Radar (SAR) imagery, geospatial analysis, and quantitative assessment to support data curation, imagery exploitation, and dataset development for machine learning model testing and evaluation. You will collaborate with engineers, data scientists, and mission analysts to ensure imagery products are prepared, standardized, and optimized for AI/ML applications.

Required Qualifications

  • Active TS/SCI clearance with eligibility for CI Polygraph (we can sponsor your CI poly if you don't already have one)
  • 4+ years of experience working with Synthetic Aperture Radar (SAR) imagery, including collection methodologies, radar phenomenology, image formation, and exploitation products.
  • Experience evaluating SAR imagery quality metrics and interpreting sensor metadata, including the effects of collection geometry (e.g., graze angle, squint angle, azimuth) on SAR phenomenology.
  • Demonstrated experience exploiting SAR imagery to detect, identify, and geolocate objects of interest.
  • Strong understanding of remote sensing principles, imagery processing, and advanced SAR exploitation techniques.
  • Excellent communication skills with the ability to effectively present SAR methodologies, imagery products, and analytical findings to both technical and non-technical audiences.
Preferred Qualifications
  • Experience applying computer vision (CV), machine learning (ML), or deep learning techniques to SAR imagery and geospatial data to support intelligence, defense, or remote sensing applications.
Key Responsibilities
  • Support the Lead SAR Scientist in evaluating emerging sensor capabilities and comparing new collection platforms with existing operational systems.
  • Assess the impact of new sensor data on existing data architectures, including metadata, file formats, schemas, APIs, and ETL processes required to ingest and integrate data into operational pipelines.
  • Evaluate data acquisition strategies, expected collection latency, available data formats, and applicable security domains for new sensor sources.
  • Develop preprocessing and standardization workflows to prepare imagery for labeling, analytics, and AI/ML model testing. This may include file format conversion, image tiling, geospatial normalization, and other data preparation activities to ensure compatibility with established data standards.