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Internship Machine Learning Quant Jobs in Virginia

Ametek

Machine Learning Engineer

Herndon, VA · Hybrid

... closely related quantitative field. * This is a hybrid role in Herndon, VA and no relocation ... internships, or realworld projects involving applied machine learning. #LI-WA1 #LI-HYBRID

Ametek

Machine Learning Engineer

Herndon, VA · On-site

... closely related quantitative field. * This is a hybrid role in Herndon, VA and no relocation ... internships, or real-world projects involving applied machine learning. #LI-WA1 #LI-HYBRID ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

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Internship Machine Learning Quant information

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

AspectInternship Machine Learning QuantData Scientist Intern
Required CredentialsStrong programming skills, basic finance knowledge, coursework in machine learningStatistics, programming, domain knowledge, coursework in data analysis
Work EnvironmentFinancial firms, hedge funds, quantitative trading teamsTech companies, startups, research labs
Industry UsageFinance, trading, quantitative researchTechnology, marketing, healthcare analytics
Common Search IntentInternship roles in finance with machine learning focusInternship roles in data science across industries

Internship Machine Learning Quant roles typically focus on applying machine learning techniques to financial data within trading and investment firms. Data Scientist Intern positions are broader, spanning various industries like tech and healthcare, emphasizing data analysis and modeling. While both require programming and analytical skills, the finance-specific knowledge is more critical for Machine Learning Quant internships.

What are the most commonly searched types of Machine Learning Quant jobs in Virginia? The most popular types of Machine Learning Quant jobs in Virginia are:
What are popular job titles related to Internship Machine Learning Quant jobs in Virginia? For Internship Machine Learning Quant jobs in Virginia, the most frequently searched job titles are:
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Internship Machine Learning Quant jobs near you
Machine Learning Engineer USC

Machine Learning Engineer USC

Connexions Data Inc

Arlington, VA

Other

Posted 5 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