Quantitative Strategist Specialist, VP – Algorithmic Solutions, Credit Risk

Job Description

Quantitative Strategist Specialist, VP | Deutsche Bank

The Tone:
This is a full-time role at Deutsche Bank, located in Mumbai. The Algorithmic Solutions (AlgoS) team, part of Group Strategic Analytics (GSA), focuses on designing and developing financial algorithms for regulatory risk measures, including credit risk weighted assets, leverage ratio, expected credit losses, and economic capital. This role is crucial for understanding new regulations and translating them into intelligent, strategic, and sustainable calculations that support accurate and transparent analysis and reporting of their impact across the firm. The position offers a challenging, varied, and multi-dimensional work environment through interaction with various divisions and diverse projects.

The TL;DR
• Role: Full Time
• Type: Full-time
• Location: In-person – Mumbai, Maharashtra, India

• Team: Algorithmic Solutions (AlgoS), part of Group Strategic Analytics (GSA)
• Mission: Design and develop financial algorithms for regulatory risk measures, with a particular focus on Credit Risk, and translate new regulations into sustainable calculations.
• Tech Stack: SAS, R, SQL, Python

What You’ll Actually Do
• Algorithmic Design: Understand new and amended capital regime regulations, translating them into intelligent, strategic, and sustainable calculations for accurate analysis and reporting.
• Business Programming: Design, document, and write algorithms in a bespoke AlgoS business language, enabling automatic creation of machine-generated code.
• Technical Build: Facilitate the creation of functional design and the actual technical build in partnership with other technology departments, ensuring precise and complete testing of changes.
• Change Governance: Run the algorithmic book of work in an Agile environment, interact with Finance and GT change functions, and ensure successful build of solutions for continuous enhancements to regulatory frameworks.
• Data Analysis: Provide ad hoc analytic services to senior stakeholders on specific topics, such as regulatory quantitative impact studies and what-if analysis for capital planning.

The Must-Haves
• Background: Master’s degree in natural sciences, math, computer science, engineering, finance, or economics.
• Experience: At least 5 years of working experience, ideally within banking, with exposure to credit risk and associated regulatory concepts.
• Skills: Engineer mind-set (curiosity, desire to change, design processes, make projects happen); ability to work autonomously and collaborate with teams that welcome and challenge new ideas; practical experience in programming (SAS, R, SQL, or Python) and working with big datasets; proven ability to leverage AI tools to enhance productivity and optimize workflows while applying critical judgment for ethical use of data and AI outputs.
• Bonus: Practical experience with Basel 4 / CRR3 and reporting frameworks such as FINREP, COREP, and Pillar 3, as well as US and European local regulations.