Quantitative Credit Actuary

Location: Bangalore, KA, IN

Are you ready to grow your career as a credit quant/actuary in a role that blends technical depth with meaningful business impact? Do you thrive on enhancing costing tools that drive real deal decisions? Are you curious about assessing profitability across diverse credit portfolios and helping shape underwriting strategy? If you enjoy working at the intersection of quantitative modelling, credit risk and collaborative business partnering — this role is for you.

At Swiss Re, we are looking for a Quantitative Credit Actuary to join our Actuarial Portfolio Management, Credit & Surety team in Bangalore, where your expertise will have a direct and meaningful bearing on costing quality and portfolio outcomes.

About the Role

As a Quantitative Credit Actuary, you will sit at the heart of business profitability — combining actuarial judgement, deep credit risk knowledge and hands-on quantitative model development to build, enhance and deploy analytical and simulation-based pricing and costing models. This is a role where your technical contributions are visible, valued and directly connected to business decisions.

You will act as a product owner for existing costing models and front-end tools, collaborating closely with full-stack developers across the full delivery lifecycle — from requirements discovery and prototyping through to user-story definition, release validation and production adoption. In partnership with Underwriting, Reserving, Claims, Finance and other key stakeholders, you will develop a comprehensive view of risk and performance and provide an independent actuarial pricing opinion.

Key Responsibilities

• Support pricing and modelling of individual deals, single risks and portfolio transactions, providing independent actuarial pricing opinions to underwriters and portfolio owners
• Develop, enhance and maintain analytical and simulation-based models used to price and assess Credit & Surety risks
• Contribute hands-on to Python-based model development, automation and deployment, ensuring solutions are robust, maintainable, scalable and appropriately documented
• Apply credit risk modelling knowledge to the development and calibration of assumptions, methodologies and parameters, including EAD, LGD and PD
• Translate stakeholder requirements into quantitative solutions, prototypes, user stories, acceptance criteria and prioritised development backlogs
• Perform model validation activities, including smoke testing and user-performance checks to ensure deployed outputs are accurate, stable and fit-for-purpose
• Drive enhancements to costing models and parameter settings aligned with Swiss Re standards and evolving business needs
• Evaluate model accuracy, stability, uncertainty and limitations, and clearly communicate implications to both technical and non-technical stakeholders
• Contribute to portfolio studies, loss trend analyses, profitability assessments and other initiatives supporting active portfolio steering

About the Team

The Actuarial Portfolio Management, Credit & Surety (APM C&S) team is a friendly, collaborative and intellectually curious group that puts the client at the centre of everything we do. We partner closely with portfolio owners to provide the framework for sound portfolio steering and deliver the insights that drive profitability.

We are passionate about data-driven outcomes and continuously seek innovative ways to tackle challenges through quantitative models and data transformation. Our team reports directly to the Head of Underwriting Excellence, Corporate Solutions, giving us strong visibility and influence across the organisation.

You will be joining a team that values rigour, creativity and openness — where your ideas are heard, your growth is supported and your work makes a tangible difference.

About You

You are a technically strong and intellectually curious professional who brings both quantitative depth and strong communication skills to everything you do. You can explain complex credit risk and modelling concepts clearly to technical and non-technical audiences alike, and you are comfortable presenting findings and recommendations to senior stakeholders.

You are collaborative by nature — building effective working relationships across multidisciplinary and multicultural teams — and you are recognised as open, dependable and delivery-oriented. You strike the right balance between technical rigour and commercial judgement, and you understand how quantitative analysis connects to real business outcomes.

We are looking for candidates who meet these requirements:

• 4+ years of experience in quantitative model development, statistical risk modelling, pricing/risk analytics or closely related fields
• Strong knowledge of credit risk concepts and modelling techniques, including PD, LGD, EAD, portfolio risk, loss distributions and model calibration
• Advanced hands-on proficiency in Python, including the development of robust, production-ready applications, model pipelines, testing frameworks, packages and automated workflows
• A quantitative academic background, such as a Master's degree in Computational Finance, Financial Engineering, Statistics, Applied Mathematics, Actuarial Science or a related discipline
• Strong written and verbal communication skills, including the ability to present complex findings through concise presentations, reports and visualisations

These are additional nice to haves:

• Familiarity with Java or C++, particularly for performance-sensitive modelling components or system integration
• Experience with credit portfolio modelling, pricing models, capital models, stress testing or portfolio risk analytics
• Knowledge of model governance, validation, deployment and production monitoring practices
• Experience collaborating with business stakeholders, developers and other technical specialists across multidisciplinary teams
• Progress toward relevant professional qualifications (e.g., CFA, FRM, CQF, IFoA, IAI, etc.)

Our company has a hybrid work model where the expectation is that you will be in the office at least three days per week.