Responsibilities: Design, develop, and implement advanced Data Science solutions leveraging statistical modeling, Machine Learning, and Deep Learning techniques. Develop predictive models, perform feature engineering, and validate model performance using industry best practices.
Numbers & Facts
Location
Charlotte, NC
Description
Our Client, an IT Services and Consultant company, is looking for a Data Scientist - Generative AI / Machine Learning for their Charlotte, NC location.
Responsibilities:
Design, develop, and implement advanced Data Science solutions leveraging statistical modeling, Machine Learning, and Deep Learning techniques.
Build and evaluate Generative AI and LLM-based solutions to address business challenges and improve operational efficiency.
Analyze large and complex datasets using SQL across Oracle (On-Prem), GCP, and AWS environments.
Work closely with business stakeholders to understand requirements, define objectives, and deliver actionable insights.
Develop predictive models, perform feature engineering, and validate model performance using industry best practices.
Collaborate with Data Engineering and MLOps teams to support model deployment and operationalization activities.
Stay current with emerging advancements in AI, Machine Learning, and Generative AI technologies.
Requirements:
Primary Skills
Strong foundation in Data Science, including:
Statistical Modeling
Machine Learning Algorithms
Deep Learning Techniques
Hands-on experience with Generative AI, Large Language Models (LLMs), and AI-driven solution development.
Strong SQL expertise with the ability to analyze and manipulate data in:
Oracle (On-Premises)
Google Cloud Platform (GCP)
Amazon Web Services (AWS)
Ability to independently solve complex business problems with minimal guidance.
Strong communication, presentation, and stakeholder management skills.
Secondary Skills
Understanding of MLOps concepts, workflows, and model lifecycle management.
Experience collaborating with MLOps teams for model deployment and monitoring activities.
Exposure to cloud-based data platforms and analytics ecosystems within GCP and AWS.