Two Sigma is a financial sciences company, combining data analysis, invention, and rigorous inquiry to help solve the toughest challenges in investment management, insurance technology, securities, private equity, and venture capital.
Our team of scientists, technologists, and academics looks beyond the traditional to develop creative solutions to some of the world’s most complex economic problems.
We are looking for creative experts who are interested in applying general machine learning and specifically deep learning techniques to many types of problems, but particularly those with large amounts of noisy data.
This role is only open to PhDs in their final year of study.
You will take on the following responsibilities:
- Develop effective techniques and infrastructure, from the initial idea to the running prototype and product
- Similar to a research environment, you will write code, use the latest machine learning tools, run experiments, and generally develop techniques and processes to improve our understanding of how financial data influences the world around us
- Partner with teams across Two Sigma to implement your ideas into their products
- Remain connected to the broader research community by partnering with internal and external collaborators and participate in relevant conferences
You should possess the following qualifications:
- Advanced degree in Computer Science, Engineering, or other STEM field
- Excellent programming skills in Python, C++, Tensorflow, PyTorch or similar languages
- Internships/work experience with machine learning, deep learning, reinforcement learning
- Background in machine learning techniques with large amounts of noisy data, curiosity in applying it to financial problems
- Relevant research experience (publications at NeurIPS, ICML, ICLR or similar are preferred)
- Experience with cloud environments and multi-machine setups
- Participation in open source community
