Financial Engineer

Moody's Analytics; Gurugram District, Bengaluru; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Moody's Analytics in India is seeking an Experienced Financial Engineer to design waterfall cash flow models for structured finance deals and support US/European securitization transactions with our modelling software.

The role requires 3–4 years in securitization, strong quantitative skills, and collaboration with global finance, data, and tech teams. Proficiency with AI tools to enhance workflows is valued. Based in Gurugram region, India, this is an on‑site opportunity.

Qualifications

• 3-4 years of securitization experience with exposure to CLOs, RMBS, CMBS, or ABS.
• Strong quantitative and analytical skills for modeling complex deal structures and cash flow waterfalls.
• Experience with SQL, Python, VBA, C#, JavaScript, and JSON is highly desirable.
• Attention to detail and ability to manage multiple priorities in a fast-paced global environment.
• Collaborative with financial engineers, data teams, and developers across global locations.
• Proficiency with AI concepts and practical use of AI tools to streamline workflows.

Responsibilities

• Develop waterfall cash flow models for structured finance deals to expand coverage and deliver analytics for global clients.
• Lead and participate in quality and productivity projects to improve modelling workflows.
• Lead tool development and enhancement initiatives with technology teams.
• Collaborate with asset class desks and client support to address client challenges and analyze securitization products.
• Engage with trustees to resolve issues and ensure accurate representation of deal terms in models.
• Share expertise across asset classes to improve content and processes.

Skills

Securitization experience

Structured finance

Cash flow modelling

Data analysis

SQL

Python

VBA

C#

JavaScript

JSON

Attention to detail

Team collaboration

Communication

AI concepts

Education

Masters in Finance/Engineering/Statistics

Tools

Proprietary modelling software

Job description

Experience level Experienced Hire

Job category Corporate Services

Line of business Asset Mgmt

Job Summary

At Moodys, we unite the brightest minds to turn today s risks into tomorrow s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are-with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we re advancing AI to move from insight to action-enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.

If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity.

Skills and Competencies

• Minimum of 3 to 4 years of relevant experience in the securitization field with hands-on exposure to Structured Finance asset classes such as Collateralized Loan Obligations, Residential Mortgage Backed Securities, Commercial Mortgage Backed Securities, or Asset Backed Securities required; background in Collateralized Loan Obligation asset class preferred
• Strong quantitative and analytical problem-solving abilities with the capability to interpret and model complex deal structures and cash flow waterfalls accurately
• Experience with data tools and scripting or programming languages such as SQL, Python, VBA, C#, JavaScript, and JSON highly desirable; candidates may be assessed on problem-solving skills and ability to write code
• Attention to detail with the ability to deliver outputs accurately within stipulated timeframes while managing multiple priorities in a fast-paced global environment
• Excellent team player with the ability to collaborate effectively with financial engineers, data teams, and developers across multiple global locations
• Good verbal and written communication skills with the ability to engage directly with trustees and cross-functional teams across client support and asset class desks private credit exposure is a plus
• Demonstrated proficiency in artificial intelligence concepts, with hands-on experience using AI tools to streamline workflows and enhance operational efficiency. Proven ability to implement AI-powered solutions to solve business challenges. Demonstrates a growing awareness of AI risk management and a commitment to responsible and ethical AI use

Education

• Masters degree in Finance, Engineering, Statistics, Mathematics, or a related quantitative field required

Responsibilities

• The Financial Engineer is responsible for waterfall cash flow modelling of structured finance deals to expand coverage and deliver high-quality analytics for global clients develop complex cash flow projection models, including deal structure setup, for US and European securitization transactions using proprietary modelling software
• Lead and participate in quality and productivity enhancement projects to improve the accuracy and efficiency of cash flow modelling workflows
• Lead and participate in modelling and updating tool development and enhancement initiatives in collaboration with technology and developer teams
• Work closely with asset class desks and client support teams to address client challenges, support new feature developments, and analyze emerging securitization products in the market
• Collaborate with financial engineers, data teams, and developers across multiple global locations to improve the coverage and quality of content offerings and business processes. Also, engage directly with trustees of structured finance transactions to resolve issues and ensure accurate representation of deal terms in models
• Contribute to cross-training within the team by sharing expertise in securitization structure and cash flow features across various asset classes