Traditional forecasting methods are insufficient for handling large volumes of data with complex noise, leading to suboptimal results. Covariance.ai's breakthrough research aims to solve this by developing advanced predictive engines that leverage diverse datasets for industry-beating forecasting.
Requirements
- 3+ years of experience in data engineering or related fields with a track record of building (coding) and scaling a data platform
- 2+ years of industry experience building ETL pipelines in a major cloud provider
- Highly proficient in python and SQL
- Advanced knowledge of databases, design patterns, OOP, and concurrency
- Knowledge of data management fundamentals and data storage principles
- Experience with AWS, orchestration platforms, and modern tech stacks
- Strong software engineering fundamentals: system design, algorithms, data structures
Responsibilities
- Build distributed systems supporting complex transformations over petabyte-scale data
- Design, implement, and maintain production cloud data pipelines for complex, disparate datasets
- Work closely with our Quants and Applied Scientists to support rigorous scientific process, rapid experimentation, and new product initiatives
Other
- Bachelor’s or advanced degree in Computer Science, math or equivalent
- Passion for intuitive data models
- Experience communicating with senior management as well as colleagues from engineering, analytics, and business backgrounds
- In-person at our NYC office strongly preferred. Remote candidates who can spend some time in-office (e.g., monthly) will also be considered.
- Free health, vision, dental insurance
