Generative AI Data Scientist

Job Description

Responsibilities

Leveraging advanced analytics and statistical techniques to extract insights from large datasets
Designing and developing robust data solutions to transform raw data into actionable insights
Conducting exploratory and descriptive analysis to solve complex business problems
Creating data visualizations to inform strategic decisions and enhance client understanding
Utilizing machine learning and artificial intelligence to drive data-driven decision making
Developing and managing data pipelines and data lakes for efficient data processing
Implementing data science algorithms and workflows to optimize data analysis
Collaborating with clients to understand their needs and deliver tailored data solutions
Applying programming languages such as Python, R, and MATLAB for data modeling and analysis
Confirming data quality and integrity throughout the data lifecycle
Engaging in predictive modeling and complex data analysis to anticipate business trends
Mentoring junior team members and fostering a collaborative team environment

What You Must Have

What Sets You Apart

Proven experience building and deploying production-grade Agentic AI solutions using frameworks like LangChain, LangGraph, CrewAI, or AutoGen.
Strong knowledge of AI interoperability protocols (e.g., MCP, A2A) and advanced Retrieval
Augmented Generation (RAG) architectures such as Graph RAG, Vectorless RAG, and Hybrid RAG.
Deep understanding of traditional AI/ML fundamentals including model building, fine-tuning, quantization, feature engineering, and model evaluation.
Foundational awareness of Responsible AI principles, security practices for safe deployments, and experience evaluating GenAI and Agentic AI applications.
Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP), familiarity with CI/CD pipelines, and relevant AI/GenAI certifications preferred.