Data Analyst and Modeling Specialist

2 days ago


Arlington, Virginia, United States Booz Allen Hamilton Full time
Transforming Complex Problems into Strategic Solutions

At Booz Allen Hamilton, we are committed to empowering our clients with the insights they need to drive transformational change. As a seasoned Operations Research Analyst, you will play a critical role in helping us achieve this mission.

About the Role

We are seeking an experienced Data Analyst and Modeling Specialist to join our team of innovative professionals. In this exciting role, you will leverage your expertise in analytical methodologies, including statistics, optimization, machine learning, and predictive analytics, to develop cutting-edge solutions for our clients.

Key Responsibilities:
  • Analyze large, complex data sets to identify trends and patterns that inform strategic decision-making
  • Develop and implement mathematical models to support a variety of client problems
  • Collaborate with cross-functional teams to design and execute experiments and test and evaluation strategies
Requirements and Qualifications

To be successful in this role, you will require:

  • 7+ years of experience in the Military
  • 3+ years of experience applying analytical methodologies, including statistics, optimization, machine learning, and predictive analytics
  • 2+ years of experience in design of experiments or test and evaluation
  • Experience with R and Python
  • A Master's degree in Operations Research, Data Science, Applied Mathematics, Statistics, Analytics, or Industrial Engineering
Benefits

We offer a comprehensive benefits package, including:

  • A competitive salary range of $67,700.00 to $154,000.00 (annualized USD)
  • Health, life, disability, financial, and retirement benefits
  • Paid leave, professional development, tuition assistance, work-life programs, and dependent care
Work Environment

This role is part of a collaborative and dynamic team that prioritizes flexibility and collaboration. You will have the opportunity to work remotely or from one of our facilities, depending on the specific requirements of the role.



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