Applied Scientist II: Cloud Cost & Efficiency (Remote)

United States Digital Space LLC; United States; Remote; USD 100,000 - 145,000; Full time

Benefits offered by this job

Market leader compensation

Comprehensive wellness programs

Generous vacation and holidays

Parental and adoption leave

Professional development opportunities

Employee networks and volunteering

Vibrant office culture

Job summary

United States Digital Space LLC is seeking an Applied Scientist II to join our growing team. You will contribute to the research, development, and deployment of machine learning models that power cost attribution and cloud efficiency at the company.

The candidate will analyze large-scale cloud usage and financial datasets, build and evaluate models, and work closely with engineering teams to bring models into production.

Qualifications

• Experience developing, training, and evaluating ML models on structured business/financial data.
• Proficiency in Python and ML libraries (PyTorch, TensorFlow, scikit-learn).
• Experience with large-scale datasets and distributed processing (Spark, Pandas).
• Strong understanding of statistics, probability, and experimental design.

Responsibilities

• Be an energetic self-starter with ownership and accountability for deliverables.
• Collaboratively build ML solutions to attribute cloud costs and resource usage.

Skills

Python

ML libraries (PyTorch, TensorFlow, sci

Spark & Pandas

Statistics & experimental design

SQL querying

Cross-functional collaboration

Tools

PyTorch

TensorFlow

scikit-learn

Spark

Pandas

CI/CD for ML

Job description

United States Digital Space LLC is seeking an Applied Scientist II to join our growing team. You will contribute to the research, development, and deployment of machine learning models that power cost attribution and cloud efficiency at the company.

The candidate will analyze large-scale cloud usage and financial datasets, build and evaluate models, and work closely with engineering teams to bring models into production.