Job Description

MORE ABOUT THIS JOB

What We Do

At Goldman Sachs, our Engineers don’t just make things – we make things possible.  Change the world by connecting people and capital with ideas.  Solve the most challenging and pressing engineering problems for our clients.  Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action.  Create new businesses, transform finance, and explore a world of opportunity at the speed of markets.

Engineering, which is comprised of our Technology Division and global strategists groups, is at the critical center of our business, and our dynamic environment requires innovative strategic thinking and immediate, real solutions.  Want to push the limit of digital possibilities?  Start here.

Who We Look For

Goldman Sachs Engineers are innovators and problem-solvers, building solutions in risk management, big data, mobile and more. We look for creative collaborators who evolve, adapt to change and thrive in a fast-paced global environment.

Transaction Banking Lending, a business unit within TxB, aims to provide comprehensive working capital and funding solutions for corporations. TxB Lending combines the strength and heritage of a leading financial institution with the agility and entrepreneurial spirit of a tech start-up. Through the use of modern technologies centered on data and analytics, we provide customers with powerful tools that are grounded in value, transparency and simplicity to improve funding and liquidity efficiency.

RESPONSIBILITIES AND QUALIFICATIONS

TxB Lending Engineering team is responsible for building data-driven decision models and processes for various business decisions through the client relationship like underwriting, pricing and collections. The team is also responsible for internal analytics like monitoring portfolio risk, projecting revenues and providing business insights. In this role you will handle the following responsibilities:

Design/evaluate predictive models and advanced algorithms for decision making using statistical modeling, feature engineering and machine learning techniques

Develop production quality code to implement and deploy these algorithms for production use
Interface with data architecture and other technology teams for production processes
Understand the business and interface with product and strategy teams in model selection and monitoring processes
Help document your assumptions and methodologies, and perform validation and testing to facilitate peer reviews and independent model validation
Build internal analytics/ dashboards for monitoring portfolio risk and providing client insights to leadership team

Basic Qualifications

BS/MS or PhD in a quantitative field – Computer Science, Mathematical Finance, Engineering, Physics,

2+ Years of experience in Mathematical Finance domain
Quantitative background including an understanding of probability and statistics
Strong programming background in compiled or scripting languages (Python, Java, etc.)
Ability to explain complex models and analysis to diverse audience

Preferred Qualifications

Either strong data science/ML experience or experience in SME lending or other loan modeling is preferred
Familiarity with statistical computing languages or packages  (pandas/numpy/scikit-learn, Tensorflow, Keras, Pytorch) 
Experience with version control and production quality code development
Familiarity with working with large datasets
Loan/Credit risk modeling or other similar financial modeling experience