Data Scientist II — End-to-End ML & Productionization

United States Digital Space LLC; San Francisco (CA); On-site; USD 152,000 - 190,000; Full time

Job summary

United States Digital Space LLC is seeking a Data Scientist to own the full model development lifecycle, from problem framing with stakeholders to production deployment and monitoring. You'll build AI solutions to mitigate risk and improve customer experience, partnering with Ops, Engineering, Product, Fraud, Compliance, and Credit teams.

Ideal candidates have 3+ years in Data Science/ML (or 2+ years with a PhD), strong Python/SQL skills, experience with ML frameworks, and a knack for

Qualifications

• 3+ years of experience in Data Science/ML roles, or 2+ years with a PhD in a quantitative field.
• Own end-to-end model development, including productionization.
• Expertise in Python programming, SQL queries, and ML-related frameworks.
• Apply statistical techniques such as hypothesis testing and A/B testing.
• Strong software engineering fundamentals with API development and production ML integration.
• Strong communication and collaboration with stakeholders.

Responsibilities

• Drive Data & AI solutions from inception to deployment to manage risk and improve customer experience.
• Own the full machine learning lifecycle — problem identification, model design, training, productionization, and monitoring.
• Partner with cross-functional teams (Ops, Engineering, Product, Fraud, Compliance, and Credit).

Skills

Python

SQL

ML frameworks

Statistics

A/B testing

Productionization

API development

Software engineering

Communication

Education

PhD in a quantitative field

MSc/PhD in Machine Learning or related field

Tools

ML frameworks

APIs

Job description

United States Digital Space LLC is seeking a Data Scientist to own the full model development lifecycle, from problem framing with stakeholders to production deployment and monitoring. You'll build AI solutions to mitigate risk and improve customer experience, partnering with Ops, Engineering, Product, Fraud, Compliance, and Credit teams.

Ideal candidates have 3+ years in Data Science/ML (or 2+ years with a PhD), strong Python/SQL skills, experience with ML frameworks, and a knack for