Corporate AI and Machine Learning Engineer

Booz Allen Hamilton is seeking a Corporate AI and Machine Learning Engineer to transform data into actionable insights. The role involves utilizing advanced analytical skills to support company-wide talent analytics efforts and develop predictive models to guide decision-making processes.

Responsibilities

• 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

Skills

• 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
• 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 and people data analytics, people processes, and people metrics, including employee experience survey design and overall workforce lifecycle listening strategies
• Knowledge of relational modeling concepts such as fact vs. dimension tables, primary or foreign keys, constraints, or slowly changing dimensions
• Ability to follow emerging team CI/CD practices in GitHub
• Master's degree in a quantitative field such as Statistics, Applied Machine Learning, Analytics, Quant Psychology, Economics, or Biostatistics

Benefits

• Health, life, disability, financial, and retirement benefits
• Paid leave
• Professional development
• Tuition assistance
• Work-life programs
• Dependent care
• Recognition awards program

Company Overview