Covariance.ai

Covariance.ai

Senior Software Engineer, Data Platform

New York · Senior

Sponsorship not specified$145k-$220kDetected 13 days ago
PythonDistributed SystemsObject-Oriented ProgrammingData StructuresAlgorithmsSQLAWSMachine LearningdbtData EngineeringLLMsStatisticsA/B TestingForecastingResearch

About the role

  • Traditional forecasting breaks under petabytes of features, megabytes of labels, and time-varying noise.
  • Our predictive engines combine a wide variety of data through rigorous scientific process.
  • We leverage alternative datasets (consumer transactions, geolocation, etc) along with private, public, external, and internal data.

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
  • system design, algorithms, data structures

Requirements

  • Bachelor's or advanced degree in Computer Science, math or equivalent
  • 3+ years of experience in data engineering or related fields with a track record of building (coding) and scaling a data platform
  • Knowledge of data management fundamentals and data storage principles
  • Experience communicating with senior management as well as colleagues from engineering, analytics, and business backgrounds
  • Experience with AWS, orchestration platforms, and modern tech stacks

Nice to have

  • Working understanding of basic probability and statistics
  • Experience implementing ML models
  • Experience with DBT
  • MS or PhD in STEM field
  • In-person at our NYC office strongly preferred.

Compensation

  • The salary range for this position is $145,000-$220,000

Benefits

  • Free health, vision, dental insurance
  • Unlimited PTO + 13 company holidays
  • Daily Grubhub lunch stipend
  • Pre-tax commuter benefits

This listing is sourced directly from Covariance.ai's careers page and normalized into a canonical job model.