Agentic & GenAI Data Analyst

TEKsystems•Durham, NC

1d•$60 - $75•Hybrid

About The Position

The Agentic & GenAI Data Analyst builds, deploys, and supervises autonomous AI agents and leverages advanced Large Language Model (LLM) frameworks to automate and enhance data pipelines, cleaning, analysis, and reporting. This role bridges traditional data analysis and artificial intelligence, focusing on transforming natural language queries into actionable insights, maintaining high data quality, and implementing human-in-the-loop oversight to ensure robust and reliable analytics.

Requirements

3+ years of experience delivering machine learning and/or generative AI projects, particularly with agentic architectures.
Experience working with large datasets, advanced data visualization, and building predictive models.
Ability to break down large, ambiguous problems into smaller, actionable agent tasks.
Experience with conversational data, text, or unstructured data.
Strong proficiency in data analysis and querying using languages and platforms such as Python and SQL (e.g., Snowflake, Redshift), including strong SQL skills in Snowflake (data modeling, query optimization, and handling semi-structured data). This includes experience in data cleaning, transformation, and validation, handling large-scale datasets efficiently.
Advanced proficiency in Microsoft Excel, including functions such as VLOOKUP, Pivot Tables, and VBA, along with familiarity with Microsoft Power Platform (Power Automate, SharePoint, Fabric).
Experience designing and implementing AI solutions, including Retrieval-Augmented Generation (RAG) pipelines and agentic AI systems, with an understanding of LLM integration, prompt design, vector databases, and orchestration frameworks (LangChain, LangGraph).
Expertise in data visualization and dashboard development, with a strong preference for Power BI, including building interactive reports and data modeling.
Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
Strong communication skills to present technical findings to non-technical audiences.
Experience in data engineering, ETL processes, and managing data pipelines.

Nice To Haves

Experience in cloud environments (AWS, GCP, or Azure).

Responsibilities

Build, fine-tune, and benchmark GenAI/LLM models and Retrieval-Augmented Generation (RAG) pipelines, automating data cleaning, feature engineering, and analytics.
Supervise agent workflows with guardrails and human-in-the-loop oversight, managing edge cases and preventing unintended actions.
Prototype and validate new agent concepts, collaborating with engineers to refine prompts and RAG strategies.
Use SQL, Python (Pandas, NumPy), platforms (Snowflake, RedShift), and visualization tools (Power BI) to analyze structured and unstructured data and uncover actionable trends.
Develop AI agents and automated workflows to streamline data extraction, processing, and reporting, while ensuring quality and strategic alignment.
Design, develop, and implement multi-agent systems for complex data workflows, integrating memory, shared state, and tools (e.g., LangChain, LangGraph).
Translate agent-driven findings and complex business questions into actionable insights for non-technical stakeholders, driving strategic decisions.
Partner with data engineers and product teams to ensure technical solutions meet business goals.