Senior Functional Developer

Crisil; Pune District; On-site; INR 3,000,000 - 5,500,000; Full time

Job summary

Crisil is seeking a Quant Developer/Engineer to join our team in Pune, focusing on translating quantitative models into production Java services. You will collaborate with model developers and Front Office quants, develop prototype models, and deploy scalable microservices in cloud-native environments.

You will work with Java, Spring Boot, Python and modern DevOps tooling, ensuring robust testing and documentation across the model lifecycle.

Qualifications

• Strong software engineering with production-grade Java services.
• Hands-on Python for quant models and prototypes.
• Ability to translate quantitative specs into working software.
• Experience with CI/CD and cloud-native environments.
• Excellent written and spoken English.

Responsibilities

• Collaborate with model developers and Front Office quants to translate requirements into implementable solutions.
• Contribute to design, development and support of quantitative models used to derive proxy or market data.
• Create clear technical and quantitative documentation of models, inputs, calculations and assumptions.
• Develop prototype implementations to validate new models before production deployment.
• Translate prototypes into production-quality Java services.
• Build scalable microservices for cloud-native environments.
• Influence architecture and design of new components and services.
• Develop applications using modern Java and Spring Boot with engineering best practices.
• Design and maintain automated unit, integration and regression tests.

Skills

Java

Spring Boot

Python

Quantitative analysis

Software engineering

English communication

Model development translation

Tools

Git

Maven

Azure DevOps

Confluence

Docker

Kubernetes/OpenShift

Linux

SQL

Job description

• Work closely with model developers and Front Office quants to understand new proxy model requirements and translate quantitative concepts into implementable solutions.
• Contribute to the design, development and support of quantitative models, particularly models used to derive or proxy market data.
• Create clear technical and quantitative documentation describing model assumptions, inputs, calculations, limitations and implementation decisions.
• Develop prototype implementations to demonstrate and validate new models before production implementation.
• Translate validated prototypes and quantitative algorithms into production-quality Java services.
• Build scalable, resilient microservices-based applications designed to run in a cloud-native environment.
• Influence technology choices and contribute to the architecture and design of new components and services.
• Develop applications using modern Java and Spring Boot, following strong software-engineering practices.
• Design and maintain automated unit, integration and regression tests, including tests that validate quantitative results.
• Work with engineers and quantitative stakeholders to ensure implementations remain consistent with their underlying model specifications.
• Contribute to CI/CD and operational readiness, using technologies such as Azure DevOps, Git, Maven, Docker, Kubernetes/OpenShift and Linux.
• Proactively identify opportunities to improve the maintainability, reliability, performance and observability of our services.
• Take ownership throughout the lifecycle, from initial model discussion and prototyping through implementation, production deployment and support.
• Share knowledge and contribute to a collaborative engineering and quantitative culture.
• Strong analytical and quantitative problem-solving skills combined with hands-on software engineering capability.
• Ability to understand mathematical or quantitative model specifications and translate them into reliable software implementations.
• Strong understanding of software design, maintainability, testing and production engineering.
• Ability to communicate effectively with both quantitative and technical stakeholders.
• Comfortable challenging assumptions, asking detailed questions and turning complex requirements into practical solutions.
• Strong focus on correctness, particularly where software implementations represent mathematical or financial models.
• Curiosity and willingness to develop deeper knowledge of financial markets, market data and quantitative modelling.
• Ability to work independently while collaborating effectively across different teams, disciplines and locations.
• Strong documentation skills and an ability to explain complex quantitative or technical concepts clearly.

Requirements

• Strong software engineering experience with Java and Spring Boot, including the development of production-quality backend services.
• Strong hands-on experience with Python, particularly for implementing, analysing and validating quantitative models and prototypes.
• Strong mathematical and analytical background, with the ability to understand and translate advanced mathematical formulas and quantitative model specifications into working software.
• Ability to take a model from quantitative specification and Python prototype through to a robust production Java implementation.
• Good understanding of algorithms, data structures, object-oriented design and software engineering principles.
• Experience developing automated unit, integration and regression tests, including validation of numerical results between prototype and production implementations.
• Experience working with relational databases and SQL.
• Familiarity with source control, CI/CD and documentation tooling such as Git, Maven, Azure DevOps and Confluence.
• Experience with Linux and containerized/cloud-native environments such as Docker and Kubernetes/OpenShift.
• Excellent written and spoken English.
• Ability to collaborate closely with model developers, Front Office quants and software engineers, translating between quantitative concepts and technical implementation.

Strongly preferred

• Experience as a Quant Developer, Quant Engineer or Software Engineer working closely with quantitative teams.
• Experience implementing complex mathematical or financial models in production systems.
• Knowledge of financial markets, particularly market data, pricing, valuation, proxy models or risk models.
• Experience working directly with Front Office quants and model developers.
• Knowledge of numerical methods, statistics, time series, optimization, financial mathematics or related quantitative disciplines.
• Experience comparing and validating Python reference implementations against production Java implementations, ensuring numerical consistency and correctness.
• Experience designing scalable microservices for computational or data-intensive workloads.