Data Analyst - Senior Software Engineer

Role & responsibilities

Position: DEVELOPER (Senior Software Engineer) Data Analyst

Experience: 5 - 10 Years

Category: IT Infrastructure

Main location: Mumbai

Responsibilities
1. RAG Architecture & Pipeline Design
• Design and maintain RAG that connects CRM to LLM to provide grounded, fact bases AI responses.
2. Vector Search & NLP
• Implement and maintain vector embeddings for entities to enable semantic search and integration with LLM for generative AI features.
3. MCP Server Development
• Design and deploy MCP to bridge LLM with existing Data sources for real-time Retrieval.
4. Generative AI Integration
• Utilize LLMs to synthesize retrieved data into accurate, user friendly natural language responses.
5. Performance Optimization
• Evaluate and optimize the end-to-end latency of search and generation.
6. Data Analysis
• Collect, analyze, and interpret large datasets to identify trends, patterns, and insights that can inform business decisions.
7. 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.
8. Project Coordination and Stakeholder Collaboration
• Collaborate with project managers, business analysts, and stakeholders to understand business requirements and translate them into technical solutions.
9. Quality Assurance and testing
• Collaborate with QA teams to validate data quality, ensure accuracy, and troubleshoot issues identified during testing.
10. Continuous Improvement
• Stay up-to on the latest tools, techniques, and best practices.
• Identify opportunities for process improvements, optimizations, and automation.
11. 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:
o Python
o Sql/Pl-Sql
o Machine learning algorithms
o RAG / Architecture
o CRM Schema
Behavioral Skills:
o Active listening
o Client focused
o Communication skills - oral & written
o Ability to deliver / Results driven
Education Level: Any Graduation/Post Graduation

Preferred candidate profile