Data Scientist

Elios Talent; United States; Remote; USD 100,000 - 130,000; Full time

Job summary

A technology studio is seeking a contract Data Scientist specialized in Microsoft Azure's AI tools. The role involves implementing RAG and semantic search pipelines, requiring deep expertise in Azure Cognitive Search and Azure OpenAI. Ideal candidates should have a degree related to Data Science and experience in delivering production-grade AI solutions. This is a remote position with flexibility to work on impactful AI projects.

Qualifications

• Experience implementing Azure Cognitive Search and OpenAI pipelines.
• Strong Python programming abilities and proven delivery of production systems.

Responsibilities

• Implement RAG pipelines on Azure (Cognitive Search + Azure OpenAI).
• Design embedding strategies, metadata, and hybrid retrieval.
• Build and expose APIs/services to integrate retrieval & generation.

Skills

Azure Cognitive Search

Azure OpenAI

NLP & Semantic Search

Python

Delivery Track Record

Vector Stores & Pipelines

Education

Degree in Data Science, Computer Science, Applied Mathematics

Job description

Data Scientist - Azure AI Stack - Contract - Remote

Hands-On Impact – Drive real results by building and shipping production RAG (Retrieval-Augmented Generation) and semantic search pipelines on Microsoft Azure.

Deep Azure Expertise – Apply practical experience with Azure Cognitive Search and Azure OpenAI (embeddings, function calling, prompt design, evaluation).

Delivery Mindset – You’ll design, implement, and hand off working solutions with clear documentation.

Role Summary

We are seeking a Contract Data Scientist (Remote) specialized in Microsoft Azure’s AI ecosystem. This is a hands-on role focused on implementing RAG/search pipelines with Azure Cognitive Search + Azure OpenAI to enable retrieval-augmented generation, semantic search, and enterprise grounding workflows.

Top Qualifications (Must-Haves)

• Azure Cognitive Search – schema/index design, enrichment pipelines, vector + hybrid retrieval, reranking, filters, relevance tuning, evaluation.
• Azure OpenAI – embeddings workflows, grounding RAG with enterprise data, function/prompt/tool patterns, safety filters.
• NLP & Semantic Search – text/PDF ingestion, chunking/sectioning, metadata design, multilingual handling.
• Programming – Python, Azure SDKs, lightweight services/APIs (FastAPI).
• Delivery Track Record – Shipped production-grade Azure RAG systems with documentation and measurable results.
• Vector Stores & Pipelines – Azure native vectors, Redis, Pinecone, Milvus, OCR, parsing, PII handling.

Preferred Credentials

• Microsoft Certified: Azure AI Fundamentals (AI-900).
• Microsoft Certified: Azure AI Engineer Associate (AI-102).
• Degree in Data Science, Computer Science, Applied Mathematics, or equivalent experience.

Responsibilities

• Implement RAG pipelines on Azure (Cognitive Search + Azure OpenAI).
• Design embedding strategies, chunking, metadata, hybrid retrieval, and reranking.
• Establish retrieval quality evaluation (gold sets, offline metrics, online checks).
• Build and expose APIs/services to integrate retrieval & generation into apps.
• Deliver clear handoff docs and partner with engineering to ensure adoption.

About Us

We are a product-focused technology studio that partners with organizations to design, build, and scale custom digital solutions. Our teams blend design thinking, engineering expertise, and AI innovation to create software that solves real problems and drives measurable business outcomes. Collaboration, creativity, and cutting-edge technology are at the core of everything we do.

Why Join Us

This is an opportunity to contribute directly to mission-critical AI solutions in a fast-moving, innovative environment. You’ll have the autonomy to implement end-to-end RAG/search pipelines, work with a highly skilled product and engineering team, and see your contributions move quickly from concept to production. As a contractor, you’ll enjoy remote flexibility while working on impactful projects that push the boundaries of enterprise AI adoption.