Position Summary

Two Sigma is a leading quantitative investment management and trading firm. The company applies a scientific approach to investing, combining cutting-edge technology, artificial intelligence, data science, and quantitative research with rigorous human inquiry to capitalize on market opportunities and deliver alpha for investors.

Our team of engineers, quantitative researchers and data scientists looks beyond the traditional to test hypotheses and develop creative solutions to some of the world's most complex economic problems.

Data Reliability Engineering (Data RE) helps engineers working with data to improve the reliability of their products and foster operational excellence through RE evaluations, short term RE engagements focused on the use of automation, and the development of data RE best practices.

As a member of the Data Reliability Engineering team, you will be responsible for maintaining the health and smooth operation of products the team owns and operates, identifying and automating areas of toil, and working with partner teams to develop and adopt reliability best practices for research and production data processes.

You will take on the following responsibilities:

• Software development of systems, services, tools and libraries.
• Improving all aspects of software reliability, including observability, operability, scalability, and availability.
• Extensive collaboration with our software engineering teams on architectural and product design, reliability, performance, support issues and improvements to our tools, processes, and software
• Identifying areas of toil, scoping out projects or automation to address it, and driving those efforts.
• Participating in a support rotation responsible for several critical production and research data pipelines.

You should possess the following qualifications:

• A bachelor's degree, equivalent or higher in computer science or another highly technical, scientific discipline.
• Proactive approach to problem identification and resolution and continuous development and automation.
• Proficiency with one or more object oriented scripting languages such as; Python, Ruby or JavaScript.
• Proven track record for automating processes together with an algorithmic approach to solving problems.
• Some knowledge of UNIX or Linux Systems.