Data Scientist

Experis Austria; Durham (NC); On-site; USD 83,000 - 90,000; Full time

Job summary

Experis is hiring an Applied AI Data Scientist for a 100% onsite role in Durham, NC. You will design and implement LLM-powered solutions for technical support workflows, including case classification, information retrieval, response drafting, summarization, and agent assistance.

Join to build AI assistants, using prompt engineering, RAG, and tool invocation, and to establish evaluation frameworks to measure accuracy, relevance, groundedness, and safety in real-world settings.

Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field.
• 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 performance in real-world applications.
• Hands-on experience with Generative AI or LLM-based applications, including understanding model limitations and the importance of evaluation and human oversight.

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.
• Create evaluation frameworks and datasets to measure accuracy, relevance, groundedness, task completion, latency, and safety.
• Run model evaluations and controlled experiments to compare prompts, models, retrieval strategies, and workflow designs.
• Work with support teams and subject matter experts to identify business needs, curate knowledge sources, and define success criteria and escalation paths.
• Analyze structured and unstructured data, including support tickets, conversations, and knowledge articles.
• Monitor AI performance, diagnose failure patterns, and iterate on 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.
• Collaborate with software and data engineering teams to integrate validated AI solutions into existing systems.

Skills

Generative AI

LLMs

LLM-powered apps

Prompt engineering

RAG

Embeddings

Vector search

Python

SQL

Statistics

Experimental design

NLP

AI APIs

Data privacy

Governance

Education

Bachelor’s/Master’s in CS/DS/Stats

Job description

Experis is hiring an Applied AI Data Scientist to create and evaluate LLM-powered solutions that improve technical support workflows. This is a 100% onsite role in Durham, NC, focused on practical AI engineering: building assistants, implementing RAG and tool usage, and proving impact with rigorous evaluation. If you enjoy turning support data into reliable AI experiences, you will have a clear path from design through validation and integration.

Compensation for this W2 position is $60 to $65 per hour. The role centers on systematic experimentation to compare prompts, models, retrieval strategies, and workflow designs, then partner across teams to ship validated solutions.

What you’ll do

• 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.
• Create evaluation frameworks and datasets to measure accuracy, relevance, groundedness, task completion, latency, and safety.
• Run model evaluations and controlled experiments to compare prompts, models, retrieval strategies, and workflow designs.
• Work with support teams and subject matter experts to identify business needs, curate knowledge sources, and define success criteria and escalation paths.
• Analyze structured and unstructured data, including support tickets, conversations, and knowledge articles.
• Monitor AI performance, diagnose failure patterns, and iterate on 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.
• Collaborate with software and data engineering teams to integrate validated AI solutions into existing systems.

What you’ll need

• 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 improvement.
• Strong understanding of prompt engineering and Retrieval-Augmented Generation (RAG), including embeddings, vector search, and model selection.
• Proficiency in Python and SQL for 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 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.

Location: Durham, NC 27709. Work arrangement: 100% onsite.

Education & 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 performance in real-world applications.
• Hands-on experience with Generative AI or LLM-based applications, including understanding model limitations and the importance of evaluation and human oversight.

Technologies: Generative AI, LLMs, Retrieval-Augmented Generation (RAG), prompt engineering, embeddings, vector search, Python, SQL, Natural Language Processing (NLP), AI APIs.