Senior Quantitative Analyst (R/ R Shiny)

Crisil; Pune District; Hybrid; INR 2,400,000 - 4,200,000; Full time

Job summary

Crisil in Pune, Hybrid - is seeking a Senior Quantitative Analyst to own the end-to-end model development value chain using R Shiny while mastering our complex ratings criteria and existing model portfolio.

This role emphasizes autonomy, rapid learning, and applying Generative AI to accelerate coding, optimize workflows, and improve analytical output for stakeholders.

Qualifications

• Expert-level R programming and production-grade R Shiny experience.
• GenAI tools integration into SDLC to boost coding and docs.
• Rapid mastery of financial methodologies and rating logic.
• Advanced degree in a quantitative field is preferred.

Responsibilities

• Lead end-to-end model lifecycle from architecture to deployment using R Shiny.
• Develop high-performance Shiny apps translating credit rating models for stakeholders.
• Upskill on proprietary ratings criteria and existing model portfolio.
• Leverage GenAI to accelerate development, debugging, and documentation.
• Possess autonomous project leadership across multiple workstreams.
• Implement robust QA frameworks to ensure governance and regulatory compliance.

Skills

R programming

R Shiny

GenAI tools

Learning agility

Quantitative skills

Education

Advanced degree in Statistics/Mathematics/Financial Engineering/Computer Science

Tools

Git

CI/CD

Python

Job description

Senior Quantitative Analyst

Location: Pune (Hybrid) Department: Methodologies Reports to: Sector Lead

Role Summary

We are seeking a highly skilled and proactive Senior Quantitative Analyst to join our team. The successful candidate will own the end-to-end model development value chain using R Shiny, while simultaneously mastering our complex Ratings criteria and existing model portfolio. We are looking for a forward-thinking professional who doesnt just follow existing workflows but actively leverages cutting-edge technologies-including Generative AI (GenAI)-to accelerate coding, optimize workflows, and enhance analytical output. This role requires a high degree of autonomy, rapid learning agility, and the ability to manage complex, multi-faceted projects with minimal supervision.

Key Responsibilities

• End-to-End Model Lifecycle Management: Lead all activities across the model development value chain, including model architecture, development, rigorous testing, validation, and deployment using the R Shiny framework.
• Domain Mastery Upskilling: Quickly acquire and apply deep subject matter expertise in our proprietary Ratings criteria and existing model portfolio to ensure all technical outputs are contextually accurate and aligned with business standards.
• Advanced Tool Development: Design and deploy sophisticated, high-performance R Shiny applications that translate complex credit rating models into intuitive tools for stakeholders.
• AI-Augmented Development: Proactively leverage Generative AI capabilities (e.g., LLMs for code generation, debugging, and documentation) to increase development velocity, improve code quality, and automate repetitive programming tasks.
• Autonomous Project Leadership: Independently manage multiple high-priority workstreams, prioritizing tasks effectively and delivering high-quality results under minimal guidance from management.
• Quality Assurance Governance: Implement robust testing frameworks to ensure the integrity of models and applications, ensuring they meet all internal governance and regulatory standards.

Required Skills Qualifications

• Technical Mastery: Expert-level proficiency in R programming and extensive experience building production-grade applications in R Shiny.
• GenAI Proficiency: Proven ability to integrate Generative AI tools into the software development lifecycle (SDLC) to enhance coding efficiency, troubleshooting, and technical documentation.
• Rapid Learning Agility: A demonstrated track record of quickly mastering complex, specialized domain knowledge (e.g., financial methodologies, regulatory frameworks, or proprietary rating logic).
• Quantitative Background: Advanced degree (Bachelors or Masters preferred) in a quantitative discipline such as Statistics, Mathematics, Financial Engineering, or Computer Science.

Additional Qualifications

• Experience in Credit Ratings, Risk Management, or Financial Modeling within a global financial institution.
• Proficiency with version control (Git) and automated deployment pipelines (CI/CD).
• Knowledge of Python or other languages used in conjunction with R for machine learning workflows.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.