Remote ML Engineer — End-to-End Production Models

IMPACT Technology Recruiting; Phoenix (AZ); On-site; USD 90,000 - 130,000; Full time

Job summary

IMPACT Technology Recruiting is seeking a data scientist for a 12-month remote contract in the United States. You will design and deploy ML models, work with Python/SQL, and collaborate with stakeholders to improve operations.

Ideal candidates have 3+ years of data science experience (5+ preferred), a Master's in a STEM field, and hands-on ML deployment experience with the full ML lifecycle and MLOps.

Qualifications

• 3+ years of professional Data Science experience (5+ preferred).
• Master's degree in a STEM field preferred
• Strong Python and SQL skills.
• Experience building and deploying machine learning models into production.
• Experience with the full machine learning lifecycle and MLOps.
• Solid understanding of statistics and machine learning algorithms.
• Experience using Git.

Responsibilities

• Design, build, validate, deploy, and monitor production machine learning models.
• Develop end-to-end ML solutions, including feature engineering, model development, testing, deployment, and monitoring.
• Partner with business stakeholders to identify opportunities where machine learning can improve operations.
• Analyze large datasets using Python and SQL to uncover actionable insights.
• Build predictive, classification, clustering, regression, forecasting, and optimization models.
• Collaborate with engineering teams to productionize and maintain machine learning solutions.
• Continuously improve model performance through experimentation, monitoring, and tuning.

Skills

Python

SQL

Git

Data science

Education

Master's degree in STEM

Tools

AWS

Snowflake

Job description

IMPACT Technology Recruiting is seeking a data scientist for a 12-month remote contract in the United States. You will design and deploy ML models, work with Python/SQL, and collaborate with stakeholders to improve operations.

Ideal candidates have 3+ years of data science experience (5+ preferred), a Master's in a STEM field, and hands-on ML deployment experience with the full ML lifecycle and MLOps.