About 0epsilon

The 0epsilon team is responsible for putting together a best-in-class mid-frequency trading platform. Data powers everything that we do, and is of the utmost priority for us to do well. We are looking for an enthusiastic and talented Quantitative Researcher, with a passion for developing a specialization in data to join our team. The ideal candidate thrives in ambiguous, fast-paced environments, is excited about building products from the ground up, has strong experience and proficiency in Python and Cython, and will be responsible for developing data ETL pipelines, cleaning, researching and maintaining features that power our machine learning algorithms for trading.

Key Responsibilities

Create robust data ETL pipelines that clean and process raw data
Research and implement features that are consumed in a machine learning trading pipeline
Write clean, well-documented code with appropriate test coverage
Assist in troubleshooting and debugging production issues
Be on-call on a rotating basis
Help establish engineering best practices and coding standards
Mentor future junior team members as we scale
Take ownership of smaller projects and features from design to deployment

Requirements

Able to thrive in the crucible of an extremely fast-paced, demanding start-up like environment
Able to bear immense responsibility for high-stakes, large-scale production infrastructure
Highly proficient in machine learning, with preference towards deep-learning architectures
High proficiency in Python and proficient in PyTorch and Polars
Experience with SQL-like databases, such as Postgres and ClickHouse database is a plus
Experience with Cython in a performance sensitive environment is a plus
Some knowledge of financial markets and instruments is a plus

Quantitative Researcher

AI overview