Senior Data Scientist — GenAI Search & RAG

ECS Corporate Services; Fairfax (VA); On-site; USD 175,000 - 205,000; Full time

Job summary

Everforth ECS in Arlington, VA seeks a Senior Data Scientist to design and optimize intelligent search and retrieval systems, applying GenAI to real-world data challenges. You will work with Elasticsearch, vector search, and RAG to improve relevance, accuracy, and decision-making outcomes.

The role emphasizes collaboration with customers and internal teams, embedding best practices, and shaping search architectures for enterprise-scale data.

Qualifications

• Hands-on experience applying Elasticsearch to search, analytics, or data science use cases.
• Strong understanding of search concepts including relevance tuning, indexing strategies, and query optimization.
• Experience with cloud environments (AWS, Azure, or GCP).
• U.S. citizen with an active Secret clearance.

Responsibilities

• Design, implement, and optimize intelligent search solutions using Elasticsearch (lexical, semantic, vector).
• Apply Retrieval-Augmented Generation (RAG) patterns to enhance LLM-driven applications.
• Consult with customers to translate objectives into AI-powered search strategies.
• Build and refine embedding strategies, indexing approaches, and query workflows.
• Evaluate and integrate LLMs and GenAI capabilities into enterprise search and analytics use cases.
• Lead knowledge-sharing sessions on GenAI, RAG, and advanced search techniques.

Skills

Elasticsearch

Vector search

RAG

GenAI

LLMs

Data science

Cloud platforms

Education

Bachelor's degree in Computer Science or Data Science

Job description

Everforth ECS in Arlington, VA seeks a Senior Data Scientist to design and optimize intelligent search and retrieval systems, applying GenAI to real-world data challenges. You will work with Elasticsearch, vector search, and RAG to improve relevance, accuracy, and decision-making outcomes.

The role emphasizes collaboration with customers and internal teams, embedding best practices, and shaping search architectures for enterprise-scale data.