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Overnight Machine Learning Quant Jobs in Washington

Ametek

Machine Learning Engineer

Herndon, VA · Hybrid

Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, Engineering, Mathematics, or a closely related quantitative field. * This is a hybrid role in Herndon ...

Ametek

Machine Learning Engineer

Herndon, VA · On-site

Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, Engineering, Mathematics, or a closely related quantitative field. * This is a hybrid role in Herndon ...

Geico

Machine Learning Engineer II

Bethesda, MD · Hybrid

$105K - $215K/yr

Bachelor's degree in Machine Learning, Computer Science, Statistics, Mathematics, or a related quantitative field. Two (2) years of experience as a Software Engineer, or related occupation. Two (2) ...

GEICO

Machine Learning Engineer II

Bethesda, MD · On-site

$105K - $215K/yr

Bachelor's degree in Machine Learning, Computer Science, Statistics, Mathematics, or a related quantitative field. Two (2) years of experience as a Software Engineer, or related occupation. Two (2) ...

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Overnight Machine Learning Quant information

What is the difference between Overnight Machine Learning Quant vs Quantitative Researcher?

AspectOvernight Machine Learning QuantQuantitative Researcher
CredentialsAdvanced degrees in CS, Math, or Stats; programming skillsSimilar; advanced degrees often required
Work EnvironmentFinancial firms, hedge funds, trading desks; fast-paced, data-drivenFinancial institutions, research labs; analytical, research-focused
Industry UsageHigh-frequency trading, algorithmic strategiesMarket analysis, model development
Work HoursOvernight shifts aligned with trading hoursStandard business hours, flexible in some cases

While both roles involve quantitative analysis and programming, Overnight Machine Learning Quants focus on developing models for overnight trading strategies, often working overnight shifts. Quantitative Researchers typically conduct broader market research and model development during regular hours. The roles overlap in skills but differ mainly in work hours and specific application areas.

What are the most commonly searched types of Machine Learning Quant jobs in Washington? The most popular types of Machine Learning Quant jobs in Washington are:
What cities in Washington are hiring for Overnight Machine Learning Quant jobs? Cities in Washington with the most Overnight Machine Learning Quant job openings:
Overnight Machine Learning Quant jobs near you
Machine Learning Engineer USC

Machine Learning Engineer USC

Connexions Data Inc

Arlington, VA • On-site

Other

Posted 14 days ago

Job description

Machine Learning Engineer

Start: IMMED

Duration: 06 - 12 months + Extension

Location: Arlington, VA

Type: W2 only

***Active Secret Clearance Required***

Position Overview

The Machine Learning Engineer will develop and validate quantitative models that translate organizational workload drivers into defensible Full-Time Equivalent (FTE) requirements across military, civilian, and contractor workforces. This role will work closely with Data Scientists, AI Engineers, and functional stakeholders to build scalable workforce planning and forecasting solutions using advanced statistical and machine learning techniques.

Education

Bachelor s Degree Required

Advanced degree preferred in:

  • Mathematics
  • Statistics
  • Econometrics
  • Economics

Required Skills

  • Machine Learning Modeling
  • Econometrics
  • Classical Regression Modeling
  • Statistics
  • Python

Preferred Skills

  • Palantir
  • Workforce Forecasting
  • Workload Modeling
  • AI and Data Testing

Day-to-Day Responsibilities

  • Build and validate quantitative workforce planning and forecasting models.
  • Translate organizational workload drivers into FTE requirements across military, civilian, and contractor populations.
  • Collaborate with Senior Data Scientists and AI Engineers to explore, analyze, and prepare data.
  • Perform feature engineering using Army personnel systems, including:
    • IPPS-A
    • DAPES
    • TAADS-R
  • Develop and calibrate regression models and plausibility banding logic.
  • Integrate scenario-planning model parameters into front-end applications.
  • Ensure model outputs are traceable, explainable, and defensible during client validation reviews.
  • Support AI and workforce analytics initiatives through statistical analysis and model testing.
  • Work with functional leads to validate assumptions, methodologies, and outputs.

Expected Deliverables

  • Automated manpower requirement determination models.
  • Data-driven workforce forecasting solutions.
  • Quantitative workforce planning outputs supported by defensible statistical methodologies.
  • Validated machine learning and regression-based forecasting models.
  • Reporting and analytics outputs supporting manpower and resource planning decisions.

Ideal Candidate Profile

  • Experience developing machine learning and statistical forecasting models.
  • Strong background in regression analysis, econometrics, and workforce analytics.
  • Proficiency in Python for data science and machine learning applications.
  • Ability to explain complex modeling approaches to both technical and non-technical stakeholders.
  • Experience working with large government or enterprise workforce datasets is highly preferred.

Apply