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Corporate AI and Machine Learning Engineer

Job in McLean, Fairfax County, Virginia, USA
Listing for: Booz Allen Hamilton
Full Time position
Listed on 2026-06-03
Job specializations:
  • IT/Tech
    Data Analyst, Data Scientist, Machine Learning/ ML Engineer, Data Science Manager
Salary/Wage Range or Industry Benchmark: 77600 - 176000 USD Yearly USD 77600.00 176000.00 YEAR
Job Description & How to Apply Below

Job Number: R0237111

Corporate AI and Machine Learning Engineer

Opportunity

To transform in today’s evolving digital world, organizations must harness data to resolve problems  an AI and Machine Learning Engineer, you thrive on using your critical‑thinking skills to dig deep into complex data and machine learning solutions, and you know how to apply your business and technical expertise to oversee the development of analytical processes, tools, and applications. You’ll have access to leading‑edge tools and resources as you develop highly original solutions for People Services and introduce new ideas that deliver deep visibility and insights.

Bring your analytical mindset and passion for change to lead the transformation of people analytics. Due to the nature of work performed within this facility, U.S. citizenship is required.

What You’ll Work On
  • Leverage advanced analytical expertise to inform data storytelling, providing recommendations that easily translate into the language of the business for action.
  • Support company‑wide talent analytics efforts across key areas such as talent acquisition, compensation, and attrition to drive decision‑making.
  • Conduct statistical analysis to identify differences and trends, and develop predictive models.
  • Work with People Services and business leaders on their team’s analytics needs, propose solutions, and develop people analytics strategies that align with company and business objectives across functional areas.
  • Communicate effectively across a highly matrixed organization and at different levels, think and act strategically, and influence key leaders.
  • Integrate with other internal analytics teams to partner on data sets which integrate the talent story with other functional analytics, including our internal enterprise analytics office, as needed.
  • Support ad‑hoc analytical requests using quantitative and qualitative people data to provide insights across the employee lifecycle to guide leader decision‑making processes aligned with their priorities.
You Have
  • 1+ years of experience using R or Python for data manipulation, statistical analysis, and machine learning model development
  • Experience utilizing SQL for querying and manipulating data
  • Experience with statistical inference, hypothesis testing, experimental design, and causal analysis
  • Experience applying experimental design and A/B testing, causal inference, time series or forecasting, survival or attrition modeling, multilevel or hierarchical models, or survey analytics
  • Experience with natural language processing techniques and large language models (LLMs)
  • Knowledge of compliance and regulatory requirements associated with data management and how to handle data with strict confidentiality
  • Ability to pick up new tools and concepts quickly such as building depth in Spark, ML engineering, and enterprise‑scale data practices
  • Ability to maintain a high level of competency in analytical principles, tools, and techniques to discover, learn, and apply new best‑in‑class advances in talent data analytics capabilities
  • Ability to translate technical results into clear insights and business recommendations for senior‑level audiences, document work, and communicate findings to technical and non‑technical stakeholders
  • Bachelor’s degree in Statistics, CS, Industrial Psychology, Organizational Psychology, Applied Mathematics, or Data Science
Nice if You Have
  • Experience with supervised and unsupervised machine learning algorithms relevant to predictive modeling, classification, regression, and clustering
  • Experience working with HRIS or ATS, survey, or people‑related datasets, including Workday, and employee lifecycle processes such as talent acquisition, talent development, workforce planning, or employee listening
  • Experience utilizing PySpark or Scala for large‑scale data processing and Azure Databricks platform and notebooks
  • Experience using MLflow for tracking or registry, model versioning, and experiment management in cloud environments, including Databricks
  • Experience using PyTorch and transformer‑based models
  • Experience leading functional projects as a people analytics subject matter expert
  • Knowledge of the government contracting business…
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