Responsibilities

1. RAG Architecture & Pipeline Design 

§  Design and maintain RAG that connects CRM to LLM to provide grounded, fact bases AI responses. 

1. Vector Search & NLP 

§  Implement and maintain vector embeddings for entities to enable semantic search and integration with LLM for generative AI features. 

1. MCP Server Development 

§  Design and deploy MCP to bridge LLM with existing Data sources for real-time Retrieval. 

1. Generative AI Integration 

§  Utilize LLMs to synthesize retrieved data into accurate, user friendly natural language responses. 

1. Performance Optimization 

§  Evaluate and optimize the end-to-end latency of search and generation. 

1. Data Analysis 

§  Collect, analyze, and interpret large datasets to identify trends, patterns, and insights that can inform business decisions. 

1. Technical Leadership 

§  Lead code reviews, ensuring adherence to coding standards, best practices, and quality requirements. 

§  Act as a technical point of contact for complex database issues, offering solutions and recommendations to resolve them. 

1. Project Coordination and Stakeholder Collaboration 

§  Collaborate with project managers, business analysts, and stakeholders to understand business requirements and translate them into technical solutions. 

1. Quality Assurance and testing 

§  Collaborate with QA teams to validate data quality, ensure accuracy, and troubleshoot issues identified during testing. 

1. Continuous Improvement  

§  Stay up-to on the latest tools, techniques, and best practices. 

§  Identify opportunities for process improvements, optimizations, and automation. 

1. Documentation and Standards 

§  Ensure adherence to data governance and regulatory requirements, including security and compliance standards. 

Contributing Responsibilities

• Design, develop, implement and maintain AI/LLM products to solve specific business use cases. 
• Implement and maintain vector embeddings for entities to enable semantic search and integration with LLM for generative AI features. 
• Design and deploy MCP to bridge LLM with existing Data sources for real-time Retrieval. 

• Design and maintain RAG that connects CRM to LLM to provide grounded, fact bases AI responses. 
• Explore and understand the CRM data, including customer demographics, behavior, and transactional data. 

• Develop and train predictive models using various machine learning algorithms and techniques. 

• Deploy models in production environments, such as CRM systems. 

• Monitor model performance, identify areas for improvement, and retrain models as necessary. 

• Generate insights and recommendations based on data analysis and modeling results. 

• Communicate insights and results to stakeholders, including business leaders. 

• Identify opportunities to improve CRM data quality, processes, and systems. 

• Collaborate with project managers, business analysts, and stakeholders to understand business requirements and translate them into technical solutions. 

• Stay current with industry trends, new technologies, and emerging methodologies in data science and CRM. 

• Excellent Communication and Listening Skills, attention to details is must

Technical & Behavioral Competencies

Python, R, SQL

Machine learning algorithms

PyTorch or TensorFlow 

Specific Qualifications:

Data Scientist

Skills Referential (Required knowledge, skills and abilities)

Technical Skills:

• Python
• Sql/Pl-Sql
• Machine learning algorithms
• RAG / Architecture
• CRM Schema

Behavioral Skills:

• ​​Active listening​ 
• ​​Client focused​ 
• ​​Communication skills - oral & written​ 
• ​​Ability to deliver / Results driven​ 

Education Level: Any Graduation/Post Graduation

Location: Mumbai