Senior Data Scientist — Remote Impact & ML Analytics

United States Digital Space LLC; Seattle (WA); Hybrid; USD 192,000 - 288,000; Full time

Benefits offered by this job

Equity

Company bonus

401(k) plan

Medical, dental & vision benefits

Wellness stipends

Job summary

United States Digital Space LLC is seeking a data scientist to build models, analyze metrics, and work closely with product and engineering to guide decision-making. The role involves applying statistical and machine learning techniques to large datasets and communicating insights clearly.

Responsibilities include collaboration across teams, data collection improvements, and monitoring key KPIs to drive business outcomes.

Qualifications

• Master's degree required in a quantitative field.
• 3+ years in data science or related occupation.
• Strong foundation in statistics and ML methods.

Responsibilities

• Build statistical models and analyze product/operational metrics.
• Collaborate with product, engineering and business teams to answer key questions with data.
• Apply ML models to large datasets to measure results and identify causal impact.
• Conduct exploratory analyses to understand user behavior for product development.
• Drive data collection and improve data sources.
• Communicate findings through clear visualizations and storytelling.
• Define and monitor key outcome metrics for teams and business growth.
• Present results to cross-functional stakeholders including PMs, software engineers, marketing, and biz dev.

Skills

Statistical methods

Machine learning methods

Numerical optimization

Integer programming

SQL

Python

Forecasting

Education

Master's degree in OR/Stats/Industrial Eng/Business Analytics/Math

Job description

United States Digital Space LLC is seeking a data scientist to build models, analyze metrics, and work closely with product and engineering to guide decision-making. The role involves applying statistical and machine learning techniques to large datasets and communicating insights clearly.

Responsibilities include collaboration across teams, data collection improvements, and monitoring key KPIs to drive business outcomes.