Generative AI Data Scientist

Role Overview

We are seeking a skilled Generative AI Data Scientist to join our high-performing team in Hyderabad, India. This position involves harnessing advanced analytics, machine learning, and AI technologies to extract actionable insights from complex datasets and drive data-centric solutions that empower business strategies.

Key Responsibilities

• Implement sophisticated statistical methods and advanced analytics to analyze voluminous datasets.
• Design and develop efficient data frameworks to convert raw information into meaningful insights.
• Perform exploratory and descriptive data analyses aimed at resolving intricate business challenges.
• Create compelling data visualizations to support strategic decision-making and enhance client comprehension.
• Adopt machine learning and AI techniques to realize data-driven business decisions.
• Build and oversee data pipelines and lakes, ensuring streamlined data processing.
• Deploy data science algorithms and workflows to improve the precision and efficiency of data interpretation.
• Partner with clients to capture their requirements and deliver customized data solutions.
• Apply programming languages such as Python, R, and MATLAB for comprehensive data modeling and analysis.
• Ensure the accuracy, quality, and integrity of data throughout its entire lifecycle.
• Carry out predictive modeling and advanced analytics to anticipate market and business trends.
• Guide and mentor junior analysts, promoting a collaborative team environment.

Required Qualifications and Experience

• Possess at least a bachelor's degree in a relevant discipline.
• Hold a minimum of four years of professional experience in data science or related fields.
• Demonstrate strong proficiency in written and spoken English.

Preferred Skills and Distinguishing Expertise

• Proven ability to architect and deploy production-level Agentic AI solutions leveraging frameworks such as LangChain, LangGraph, CrewAI, or AutoGen.
• In-depth understanding of AI interoperability protocols including MCP and A2A, along with advanced retrieval augmented generation architectures like Graph RAG, Vectorless RAG, and Hybrid RAG.
• Comprehensive knowledge of core AI and machine learning principles including model creation, fine-tuning, quantization, feature engineering, and model validation.
• Awareness of Responsible AI guidelines, security protocols for safe AI deployment, and practical evaluation of Generative and Agentic AI applications.
• Hands-on experience with at least one leading cloud platform (AWS, Azure, or GCP), familiarity with CI/CD methodologies, and possession of relevant AI or Generative AI certifications are highly valued.