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Form of work
SalaryAt 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 is looking for an Applied Artificial Intelligence Strat (Applied AI Strat) to join our Applied Artificial Intelligence Team. As an Applied AI Strat, you will use your advanced knowledge of computer science, statistics, artificial intelligence and machine learning to develop and deploy AI-based quantitative technologies that will help drive revenue generation and innovation in the firm.
In this role, you will have the opportunity to collaborate with different teams and divisions on innovative projects, blending artificial intelligence and quantitative finance, e.g. time series forecasting, market making and pricing. As an Applied AI Strat, you will help address the unique challenges that arise in machine learning systems within the financial domain. Join us in redefining the boundaries of what's possible at the intersection of quantitative finance and artificial intelligence!
Responsibilities
- Design and deploy scalable AI models to drive commercial outcomes.
- Conduct experimentation to improve model performance.
- Communicate verbally and in-writing to both strats and non-strats.
- Collaborate effectively with colleagues to advance production of machine-learning systems and applications.
- Developing, testing, and maintaining high-quality, production-ready code.
- Demonstrating technical leadership by taking charge of cross-team projects.
- A Master's or Ph.D. degree in Computer Science, Machine Learning, Statistics, Engineering, Quantitative Finance, or equivalent relevant industry experience.
- A minimum of 3+ years of AI/ML experience in the industry that demonstrates your expertise.
- Programming experience in Python and strong knowledge of data structures, algorithms, and software engineering practices.
- Excellent understanding of machine learning techniques and algorithms, and experience with common data science toolkits.
- Strong verbal and written communication skills.
- Curiosity, ownership and willingness to work in a collaborative environment.
ABOUT GOLDMAN SACHS
At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.
We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers.
We're committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://careers/footer/disability-statement.html
© The Goldman Sachs Group, Inc., 2023. All rights reserved.
Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Veteran/Sexual Orientation/Gender Identity
