Data Scientist (Machine Learning)

Role overview

Design, build, deploy, and monitor production machine learning solutions that address large-scale operational business challenges. Own the full machine learning lifecycle—from partnering with stakeholders to ongoing optimization.

Responsibilities

• Design, build, validate, deploy, and monitor production ML models
• Deliver end-to-end ML solutions including:
  • feature engineering
  • model development
  • testing
  • deployment
  • monitoring
• Partner with business stakeholders to find opportunities for ML-driven operational improvements
• Analyze large datasets using Python and SQL to derive actionable insights
• Build and apply models including predictive, classification, clustering, regression, forecasting, and optimization
• Collaborate with engineering teams to productionize and maintain ML solutions
• Improve performance continuously via experimentation, monitoring, and tuning

Requirements

• 3+ years professional Data Science experience (5+ preferred)
• STEM master’s preferred
• Strong Python and SQL skills
• Experience building and deploying ML models in production
• Experience across the full ML lifecycle and MLOps
• Solid understanding of statistics and machine learning algorithms
• Experience using Git

Nice to have

• AWS (preferred) or Azure/GCP
• Snowflake and experience with modern cloud data platforms
• Experience with experiment tracking/model lifecycle management (including Snowflake-related tooling)
• Background in operational optimization or forecasting models

Location / schedule

• Remote (U.S. candidates preferred) working MST, CST, or PST hours

Contract

• 12-month contract with strong potential for extension