Data Scientist

Experis Technology Group; Durham (NC); On-site; USD 125,000 - 135,000; Full time

Job summary

Experis Technology Group seeks an experienced Applied AI Data Scientist in Durham, NC to design and deploy LLM-powered solutions for technical support workflows. This role emphasizes Generative AI, RAG, evaluation, and responsible AI practices, with onsite work and competitive pay.

You will analyze support data, develop evaluation frameworks, and collaborate with product, engineering, and support teams to deliver accurate, trustworthy AI assistance in real-world environments.

Qualifications

• Experience with Generative AI and LLM-powered applications.
• Experience building or evaluating AI assistants with systematic testing and human review.
• Strong understanding of prompt engineering, RAG, embeddings, vector search, and model selection.
• Proficiency in Python and SQL for data analysis, prototyping and evaluation.
• Knowledge of statistics, experimental design, ML, and model performance measurement.
• Familiarity with NLP and text data preparation and analysis.
• Experience with AI APIs, frameworks, or orchestration tools.
• Understanding of responsible AI, data privacy, security, and governance.

Responsibilities

• Design and develop LLM-powered solutions for technical support workflows, including classification, retrieval, drafting, summarization, and agent assistance.
• Build and enhance AI assistants using prompt engineering, RAG, and orchestration techniques.
• Develop evaluation frameworks and datasets to measure AI accuracy, relevance, groundedness, task completion, latency, and safety.
• Conduct model evaluations and controlled experiments to compare prompts, models, retrieval strategies, and workflow designs.
• Collaborate with support teams and subject matter experts to identify business needs and establish success criteria.
• Analyze structured and unstructured data from tickets, conversations, and knowledge articles.
• Monitor AI performance, investigate failures, and improve prompts, retrieval methods, data quality, and safeguards.
• Apply responsible AI practices including privacy, security, transparency, human oversight, and bias testing.
• Communicate findings and recommendations to technical and non-technical stakeholders.
• Partner with software and data engineering teams to integrate AI solutions into existing systems.

Skills

Generative AI

LLMs

RAG

Prompt engineering

Python

SQL

Education

Bachelor's or Master's degree in Data Science/CS/Statistics/Math

Tools

Embeddings

Vector search

Job description

We are seeking an experienced Applied AI Data Scientist to develop intelligent, reliable AI solutions that improve technical support workflows. This role focuses on Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI evaluation to automate support tasks and deliver accurate, trustworthy results.

The ideal candidate will combine strong data science fundamentals with hands‑on experience building and evaluating LLM‑powered applications. You will collaborate with support specialists, subject matter experts, product teams, and engineers to develop practical AI solutions that improve efficiency, accuracy, and the overall support experience.
Location: Durham, NC 27709
Work Arrangement: 100% Onsite
Pay Rate: $60- $65//hour on W2

Key Responsibilities

• Design and develop LLM‑powered solutions for technical support workflows, including case classification, information retrieval, response drafting, summarization, and agent assistance.

• Build and enhance AI assistants using prompt engineering, tool calling, RAG, and orchestration techniques.

• Develop evaluation frameworks and datasets to measure AI accuracy, relevance, groundedness, task completion, latency, and safety.

• Conduct model evaluations and controlled experiments to compare prompts, models, retrieval strategies, and workflow designs.

• Collaborate with support teams and subject matter experts to identify business needs, curate knowledge sources, and establish success criteria and escalation paths.

• Analyze structured and unstructured data, including support tickets, conversations, and knowledge articles.

• Monitor AI performance, investigate failure patterns, and improve prompts, retrieval methods, data quality, and safeguards.

• Apply responsible AI practices, including data privacy, security, transparency, human oversight, and bias testing.

• Communicate findings, technical limitations, and recommendations to technical and non‑technical stakeholders.

• Partner with software and data engineering teams to integrate validated AI solutions into existing systems.

Required Technical Skills

• Hands‑on experience with Generative AI, LLMs, and LLM‑powered applications.

• Experience building, testing, or evaluating AI assistants using systematic testing, human review, error analysis, and iterative improvements.

• Strong understanding of prompt engineering, Retrieval‑Augmented Generation (RAG), embeddings, vector search, and model selection.

• Proficiency in Python and SQL for data analysis, prototyping, and evaluation.

• Strong knowledge of statistics, experimental design, machine learning, and model performance measurement.

• Familiarity with Natural Language Processing (NLP) and text data preparation and analysis.

• Experience working with AI APIs, frameworks, or orchestration tools.

• Understanding of responsible AI, data privacy, security, and governance practices.

Preferred Qualifications

• Experience working with technical support, customer service, support tickets, or knowledge management systems.

• Familiarity with cloud data platforms, data visualization, and production AI monitoring.

• Experience defining evaluation metrics and improving LLM response quality, reliability, and groundedness.

• Knowledge of data governance and responsible AI principles.

Education and Experience

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field, or equivalent practical experience.

• Minimum 7 years of professional experience in data science, applied machine learning, or a closely related field.

• Demonstrated experience delivering data science or AI solutions and evaluating their performance in real‑world applications.

• Hands‑on experience with Generative AI or LLM‑based applications, including an understanding of model limitations and the importance of evaluation and human oversight.