AI and Data Science Engineer III

Deloitte Deloitte · Consulting

AI and Data Science Engineer III role at Deloitte's Government & Public Services practice, focusing on translating mission challenges into scalable data science solutions. Responsibilities include technical leadership, model development, production pipeline oversight, and client-facing advisory in a government environment. Requires experience in data science, ML model development, cloud platforms, and a Top Secret clearance.

What you'd actually do

  1. Lead the technical direction of analytical projects, including defining research problems, developing execution plans, assigning work across junior team members, and reviewing models and code for quality and rigor
  2. Advise government stakeholders on the feasibility of analytical solutions, evaluate technical approaches, and own model validation, testing, and performance assessment methodologies for assigned workstreams
  3. Design, build, and maintain production-grade extract, transform, and load (ETL) and DataOps pipelines, predictive models, and anomaly detection solutions supporting mission-critical trade and border data platforms
  4. Apply machine learning, statistical modeling, feature engineering, natural language processing (NLP), regression, classification, anomaly detection, and causal analysis techniques to develop tools for trade enforcement, risk detection, and operational efficiency
  5. Represent the data science function in client-facing forums by translating quantitative findings into actionable recommendations for audiences ranging from frontline analysts to executive leadership

Skills

Required

  • Python
  • Structured Query Language (SQL)
  • cloud platform environment (AWS, Azure, or GCP)
  • Active Top Secret security clearance

Nice to have

  • MLOps
  • model monitoring
  • continuous integration and continuous deployment (CI/CD)
  • natural language processing
  • generative artificial intelligence
  • large language model applications
  • supporting public sector, government, or regulated environments

What the JD emphasized

  • production-grade
  • model validation
  • testing
  • performance assessment
  • production-grade extract, transform, and load (ETL) and DataOps pipelines
  • predictive models
  • anomaly detection solutions
  • machine learning
  • statistical modeling
  • feature engineering
  • natural language processing (NLP)
  • regression
  • classification
  • anomaly detection
  • causal analysis
  • client-facing forums
  • quantitative findings
  • actionable recommendations
  • Active Top Secret security clearance

Other signals

  • production-grade pipelines
  • deploying machine learning models
  • client-facing technical advisory