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Senior Data Scientist AI Engineer


Job Location:

Greenville, NC - USA

Monthly Salary: Not provided by the employer
Posted: 23 June 2026 (30+ days ago)
Application Deadline: 20 September 2026
Vacancies: 1 Vacancy

Job Summary

Senior Data Scientist / AI Engineer

Location: Greenville SC (Hybrid 3 days onsite per week)
Duration: Long-Term Contract (Initial 1-year term with extension potential)
Employment Type: W2 or C2C

Overview

A leading global manufacturer is expanding its AI organization and seeking a Senior Data Scientist with strong experience in Generative AI Agentic AI and machine learning solutions. This role will focus on designing developing testing and deploying AI-powered applications that drive business value across multiple operational areas.

The team has rapidly progressed from early AI experimentation to delivering business-facing AI solutions and is now scaling those capabilities across the organization.

Key Responsibilities

Design develop test and deploy Agentic AI solutions into business environments.
Build and maintain AI-powered applications chatbots and autonomous agents.
Develop machine learning models and advanced analytics solutions to address complex business challenges.
Partner with business stakeholders to identify opportunities for AI-driven improvements.
Analyze large and diverse datasets to generate actionable insights.
Design and execute experiments to validate model performance and optimize outcomes.
Monitor maintain and enhance AI models operating in production environments.
Support AI operations troubleshooting and continuous improvement initiatives.
Mentor junior team members and contribute to AI and data science best practices.

Current AI Focus Areas

Conversational AI solutions built on structured and unstructured business data.
Natural language interfaces for analytics and numerical data exploration.
AI-driven business process automation and workflow optimization.

Technical Environment

Programming & Data Science
Python
Pandas
NumPy
PySpark
Apache Spark

Machine Learning & AI
Generative AI
Large Language Models (LLMs)
Agentic AI
LangChain
LangGraph
Model Context Protocol (MCP)
Scikit-learn

Cloud & Infrastructure
Microsoft Azure
Kubernetes

Application Development
Streamlit
React

Analytics & Reporting
Power BI

Preferred Exposure
Databricks
Dataiku

Required Qualifications

Bachelors degree in Data Science Computer Science Statistics Engineering or related field.
Masters degree or PhD preferred.
5 years of experience in Data Science Artificial Intelligence or Machine Learning.
Strong Python development experience.
Hands-on experience building Generative AI solutions including LLMs chatbots and AI agents.
Experience integrating AI applications with OpenAI or similar foundation model platforms.
Experience with cloud platforms preferably Azure.
Experience working with big data technologies such as Spark and PySpark.
Experience with containerization and orchestration technologies such as Kubernetes.
Strong communication skills and ability to translate business requirements into technical solutions.

Preferred Qualifications

Experience deploying AI solutions into production environments.
Experience leading AI projects from concept through implementation.
Ability to communicate complex technical concepts to non-technical stakeholders.
Experience mentoring junior data scientists or engineers.
Track record of delivering measurable business impact through AI and analytics initiatives.

Team Structure

Cross-functional AI team of approximately 7 members.
Includes program management software engineering and data science professionals.
Collaborative environment with strong interaction between AI software engineering and business stakeholders.

Work Environment

Hybrid schedule with core onsite collaboration Tuesday through Thursday.
Some team members choose additional onsite days to access higher-bandwidth data resources.
Approximately 65% new development and 35% support enhancement and operational activities.

Interview Process

  1. Initial screening interview.
  2. Technical and team interview.
  3. Final stakeholder interview.