Quant jobs / Deutsche Bank

Corporate Banking Capital Strats

An associate-level strat building capital, expected credit loss and forecasting analytics for the corporate bank. It uses mainly Python and C++ within a controlled, well-documented environment.

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

Build forecasting tools for capital, expected credit loss and risk-weighted assets
Source and validate default, recovery and risk data
Develop and test Python and C++ analytics libraries
Support model calibration and scenario analysis
Help with automation, release work and production support

What they ask for

Required

Quantitative degree background
2+ years of hands-on Python
Working C++ concepts (OOP, pointers, data structures)
SQL and relational databases
Probability, linear algebra, statistics and optimisation

Preferred

Oracle or MySQL database design
Econometrics or data science
Banking products, credit risk, regulatory capital or ECL knowledge

Education: Engineering, CS, maths, statistics, physics, finance, economics or similar quantitative degree
Experience: At least two years of Python development
Languages and tools: Python
C++
SQL
Oracle
MySQL
Markets: credit

How to prepare

Build an expected credit loss calculator from PD, LGD and EAD inputs in Python
Learn how risk-weighted assets are computed under Basel rules
Practise SQL schema design for risk and default data
Write a small C++ module and connect it to Python

What to study

The Risk Quant roadmap sets out the stages for this kind of role, with free resources for each.

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Apply

Read the full posting on Deutsche Bank’s site before applying: requirements, location and pay can change after we check them.

View the posting on Deutsche Bank’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with Deutsche Bank and doesn’t handle applications.