Data Scientist
Maganti IT Resources, LLCAbout the role
Lead Data Scientist
Charlotte Onsite
US Citizen only
Job Description: Data Scientist / Generative AI Specialist
Position Overview
We are seeking a highly motivated and results-driven Data Scientist with Generative AI expertise to join our growing team. This role requires a professional with a strong foundation in traditional Data Science, including statistical modeling, Machine Learning (ML), and Deep Learning (DL), while also possessing hands-on experience with modern Generative AI and Large Language Model (LLM) solutions.
The ideal candidate will have excellent analytical and problem-solving skills, strong SQL expertise, and the ability to work independently with minimal supervision. This position is highly stakeholder-facing and requires someone who can translate business problems into scalable data-driven solutions.
Key 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.
Required Skills & Qualifications
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.
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, 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.
Qualifications
- Strong foundation in Data Science, including Statistical Modeling, Machine Learning Algorithms, and 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, GCP, and AWS.
- Ability to independently solve complex business problems with minimal guidance.
- Strong communication, presentation, and stakeholder management skills.
Skills mentioned
About Maganti IT Resources, LLC
Maganti IT is an engineering and software delivery firm built on a simple idea: teams move faster when they have fewer things to negotiate and fewer decisions to second-guess. We define the architectural standards, security boundaries, and release discipline early, so our engineers build without cognitive overload, with accountability, and toward predictable outcomes. That discipline isn't accidental. It's designed, and it's how we help organizations scale execution across the US and India in AI, Data, and Software Engineering, modernize legacy systems safely, and deliver outcomes leaders can trust.