MORE ABOUT THIS JOB
The Inventa team of strategists works closely with trading to develop quantitative medium-frequency signals and trading strategies for risk management, by processing a wide range of data sets and applying cutting-edge modelling techniques. Python is our primary language and we draw heavily on its ecosystem of services and libraries such as pandas, sklearn, scipy, numpy, jupyter, streamlit, matplotlib, bokeh, dask, flask, testplan and pymongo. We make use of the best technology for each problem and we are always keen to move forward, upgrade/update our tech stack and explore new solutions available.
Why Join Inventa?
In this role, your impact will be to design and build services, libraries and tools for both signal research and execution. This will include building resilient data processing pipelines (both streaming and batch), a distributed backtesting/simulation framework, tools for portfolio analytics and integrations with firm systems. Key challenge will be to develop solutions that are both reliable and scalable and make it possible to explore new ideas and seize commercial opportunities quickly. While your focus will be tech enhancement and innovation, you will be working along with the business within a close-knit global team and contribute to signal development front-to-back, including building financial markets knowledge, and doing hands-on modelling and research.
RESPONSIBILITIES AND QUALIFICATIONS
Responsibilities
- Work very close to the business to design and build key components of our tech ecosystem for both signal research and execution
- Hands-on research and development of trading strategies with the team
- Collaborate efficiently within a diverse global team that iterates fast
- Think commercially and identify solutions that maximize return on investment, considering utility as well as costs (incl maintenance costs)
- Work in a fast-paced environment as a self-starter
Basic Qualifications
- A Bachelor's degree (Masters/PhD a plus but not mandatory) in a computational field (Computer Science, Software Engineering, Applied Mathematics, or in a related quantitative discipline)
- Excellent programming skills in Python
- Experience working with NoSQL databases (e.g. MongoDB)
- Excellent communication skills; ability to build consensus
- Interest in financial markets
Preferred Qualifications
- Financial Services industry experience (in particular as a quantitative developer)
- Experience in statistical modelling or machine learning
- Experience using libraries from Python's data science ecosystem (e.g. pandas, sklearn, matplotlib, bokeh, flask, streamlit)
- Experience with stream-processing systems (e.g. Kafka).
ABOUT GOLDMAN SACHS
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:// www.goldmansachs.com/careers/footer/disability-statement.html
© The Goldman Sachs Group, Inc., 2021. All rights reserved.
Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Veteran/Sexual Orientation/Gender Identity
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