Principal Data Scientist

Job summary

Description: About Us Esi*** is a modern digital services company that partners with government agencies to improve the lives and protect the well-being of all Americans, from veterans and service members to children, families, and seniors.

Benefits

Qualifications

• Collaborate closely with ML engineers, data engineers, platform teams, and cross-functional partners to develop and maintain the infrastructure and governed cloud environment required for AI/ML operations.
• Create, maintain, and improve documentation for methodologies, code, assumptions, experiments, evaluation artifacts, and decisions, including documentation of AI
• Required
• Master’s degree in computer science, data science, statistics, mathematics, or a related field.
• 12+ years of experience in data analysis, data modeling, data profiling, and data management, with strong analytical, problem-solving, and critical-thinking
• for assigned systems and data.
• Preferred
• Experience supporting federal, public sector, healthcare, or other regulated data, analytics, oversight, reporting, or public transparency programs.
• Experience with natural language processing (NLP), computer vision (CV), deep learning, and neural networks.
• Knowledge of retrieval-augmented generation patterns, vector search, conversational analytics experiences, and AI gateway or governed endpoint patterns.
• Hands-on experience developing and deploying machine learning workloads within the Databricks platform or comparable modern cloud platforms such as AWS.
• Understanding of software development principles and best practices, including infrastructure-as-code and observability tooling.

Responsibilities

• Lead data science work across structured and unstructured program data, including data collection, processing, cleaning, profiling, and preparation for analysis and modeling on a governed data platform.
• Design, develop, train, evaluate, and refine machine learning models and AI services, selecting appropriate algorithms and techniques for specific customer and mission needs.
• Support deployment, monitoring, and maintenance of model performance in cloud environments using model lifecycle management, model serving, vector search, model evaluation, and related MLOps tooling.
• Plan and conduct proofs of concept and capability-gate evaluations that assess accuracy, governance integration, cost, operational overhead, and alignment to customer policy before scaling new AI capabilities.
• Embed responsible AI and equity

Skills

Degrees

Languages

Travel

Industry

Company size

Contract length

Security clearance