Quantitative Research Engineer

Numerai

Numerai is a new kind of hedge fund powered by a decentralized network of machine learning models. Every week, thousands of data scientists from around the world compete in the (Use the "Apply for this Job" box below). data science tournament to model our dataset and predict the global stock market, earning staking rewards in the NMR cryptocurrency based on their performance. Collectively, these staked predictions form the Meta Model which controls the portfolio of the Numerai hedge fund.

We are looking for talented and motivated data scientists, data engineers, and machine learning researchers to help us capture all of the data in the world and convert it into alpha.

• Python (Pandas, Numpy, Scikit-Learn)
• AWS (S3, EC2, Batch)
• Airflow
• Terraform, Docker
• Postgres, MySQL

Your role as a quantitative research enginer is to work on all of the systems that support the Numerai data, research, and trading pipeline.

You will be asked to implement and test new risk models, determining their effect on our portfolio performance and other statistics.

You will implement new portfolio management and trade execution strategies, and write research reports about the results before finally product ionizing them.

As a senior engineer, you will be expected to own and lead major projects while actively raising the engineering bar across the entire organization. You will work with other senior engineers to architect robust and performant systems and processes.

• Integrate a new risk model into our portfolio management framework and write a research report on its benefits, deciding if we product ionize it or not.
• Research, implement, and test alterations to the trading strategy in an effort to improve performance.

• Experience training and deploying machine learning models
• Experience with quant finance data
• Experience building data platforms
• Excellent written communication (design docs, specs, documentation, code reviews, post-mortems)
• Extreme ownership
• Good general systems knowledge and debugging skills