The Quantitative Research Intern will develop data ETL pipelines, research features for machine learning trading, and assist in code maintenance and best practices.
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 Intern, 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
Top Skills
Clickhouse
Cython
Polars
Postgres
Python
PyTorch
SQL
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