AI ML & Agentic Data Scientist

Qualifications

• Deep, demonstrable experience in applying ML models (, churn prediction, network
• optimization, fraud detection, etc.) preferably within the Telco industry
• Proven hands-on experience in building sophisticated, multi-step, and autonomous AI agents using
• industry-standard Python libraries like Lang Chain or Crew AI
• Lang Chain: Expertise in creating chains, defining custom tools, managing conversational memory,
• Expert-level proficiency in Python is essential for both ML development and framework
• Strong understanding of Telco business processes and data landscape
• High proficiency in data manipulation and preparation using libraries like Pandas
• Expert ability to write complex and efficient queries using SQL
• Experience working within the Microsoft Azure, Databricks environment for data processing
• (Spark), Agent bricks and MLflow lifecycle for model tracking and deployment
• Core Skills: Data Science, MLOps, Agentic Framework like LangChain, Azure, Databricks

Responsibilities

• and utilizing diverse Language Models (LLMs)
• Crew AI: Experience in orchestrating multi-agent systems, defining roles, tasks, and hierarchical
• Experience with the entire MLOps lifecycle, including feature engineering, model training,
• performance monitoring, and model serving

Full Description

Role name: AI ML & Agentic Data Scientist

Work site: Atlanta, GA (Onsite)

Contract Role

Deep, demonstrable experience in applying ML models (, churn prediction, network

optimization, fraud detection, etc.) preferably within the Telco industry.

Proven hands-on experience in building sophisticated, multi-step, and autonomous AI agents using

industry-standard Python libraries like Lang Chain orCrew AI

• Lang Chain: Expertise in creating chains, defining custom tools, managing conversational memory,

and utilizing diverse Language Models (LLMs).

• Crew AI: Experience in orchestrating multi-agent systems, defining roles, tasks, and hierarchical

communication structures.

Expert-level proficiency in Python is essential for both ML development and framework

implementation.

Experience with the entire MLOps lifecycle, including feature engineering, model training,

performance monitoring, and model serving.

Strong understanding of Telco business processes and data landscape

High proficiency in data manipulation and preparation using libraries like Pandas

Expert ability to write complex and efficient queries using SQL.

Experience working within the Microsoft Azure, Databricks environment for data processing

(Spark), Agent bricks and MLflow lifecycle for model tracking and deployment

Core Skills: Data Science, MLOps, Agentic Framework like LangChain, Azure, Databricks