Lead Federal AI Engineering and Data Solutions

KPMG LLP; McLean (VA); On-site; USD 150,000 - 190,000; Full time

Job summary

KPMG LLP in McLean, VA is seeking a Lead Specialist to join our Federal Advisory practice, driving data and AI engagements from objectives to delivery. You will lead multi-disciplinary workshops and coordinate with clients to define problems and design high-level analytical solutions.

You will oversee data discovery, ETL/ELT processes, and the creation of analytics and ML models across all development stages, manage complex workstreams and budgets, report key metrics, and travel as required to

Qualifications

• Experience leading AI/data science engagements for complex programs.
• Strong knowledge of data discovery, ETL/ELT, and data governance.
• Experience with NLP, machine learning, and information retrieval.
• Proficiency in distributed computing and big data platforms.
• Experience with cloud infrastructure and scalable analytics.

Responsibilities

• Plan, lead, and execute delivery of data/AI engagements.
• Lead workshops and cross-functional teams to identify business opportunities and design solutions.
• Discover data sources and manage data requests; lead data ingestion.
• Oversee analytics and ML models from design to deployment.
• Manage complex workstreams, budgets, and client expectations.
• Define, monitor, and report key business metrics and dashboards.
• Travel as required to support firm engagements.

Skills

Artificial Intelligence

Data Science

NLP

Machine Learning

Cloud Computing

Education

Bachelor's degree in a technical field

Tools

Hadoop

Spark

PySpark

Hive/Impala

Redshift

AWS

Azure

GCP

REST APIs

HTML5/JS

Job description

KPMG LLP in McLean, VA is seeking a Lead Specialist to join our Federal Advisory practice, driving data and AI engagements from objectives to delivery. You will lead multi-disciplinary workshops and coordinate with clients to define problems and design high-level analytical solutions.

You will oversee data discovery, ETL/ELT processes, and the creation of analytics and ML models across all development stages, manage complex workstreams and budgets, report key metrics, and travel as required to