Lead Data Scientist — Strategic ML & Impact

Compass; Seattle (WA); On-site; USD 176,000 - 195,000; Full time

Benefits offered by this job

Bonuses & RSUs

401(k) plan with match

Medical, dental and vision insurance

Paid vacation & holidays

Parental leave

Commuter program

Life & disability insurance

EAP & caregiver support

Job summary

Compass is seeking a Lead Data Scientist in Seattle to guide the data science team, architect scalable models, and partner with business and engineering leaders to drive strategic insights and product innovation.

You will mentor data scientists, apply time-series, NLP, and causal inference techniques, and communicate complex results to C-level stakeholders while upholding clean code and MLOps standards.

Qualifications

• Master’s degree or PhD in a quantitative field.
• 5+ years of data science experience leading end-to-end projects.
• Expertise in time-series forecasting, deep learning and causal inference.

Responsibilities

• Lead end-to-end development, validation, and deployment of predictive models.
• Design data-driven research to analyze factors affecting business outcomes.
• Collaborate with executives and engineering to translate goals into analytical frameworks.
• Communicate complex methodologies and findings to both technical and non-technical audiences.
• Mentor junior data scientists and promote best-practice data science and MLOps.

Skills

Time-series forecasting

Deep learning

Causal inference

MLOps

End-to-end data science

Leadership

Cross-functional collaboration

Communication

Education

Master’s or PhD in a quantitative field

Tools

Python

SQL

Job description

Compass is seeking a Lead Data Scientist in Seattle to guide the data science team, architect scalable models, and partner with business and engineering leaders to drive strategic insights and product innovation.

You will mentor data scientists, apply time-series, NLP, and causal inference techniques, and communicate complex results to C-level stakeholders while upholding clean code and MLOps standards.