Staff Data Scientist - Shape Smarter Experiences with Data

Way; San Francisco (CA); Hybrid; USD 190,000 - 260,000; Full time

Benefits offered by this job

Equity

Full health/dental/vision

Travel stipend

Office in SF/Austin/Paris

Job summary

Way is building the AI, data, and infrastructure layer for the experience economy, with offices in Austin, San Francisco, and Paris. We’re seeking a Staff Data Scientist to turn data across the platform into trusted insights, models, and decision systems that improve pricing, merchandising, personalization, and automation.

You will own data foundation and work closely with Product and Engineering to ship production-ready data products, while operating with ambiguity and high ownership.

Qualifications

• Significant experience applying data science to real product or marketplace problems.
• Experience shipping models, experiments, or decision systems that drove business impact.
• Experience building a data and analytics foundation from raw data to production-ready datasets.
• Strong SQL and Python skills with statistical rigor.

Responsibilities

• Help shape the future by turning platform data into trusted insights, models, and decision systems.
• Build and own data analytics foundation, integrating product, transactional, customer, and partner data.
• Establish core metrics and data models for consistent business understanding.
• Identify opportunities to apply data science across the Way platform and ship measurable value.

Skills

SQL

Python

Statistics

Experimentation

Forecasting

Model evaluation

Product judgment

Ownership

Job description

Way is building the AI, data, and infrastructure layer for the experience economy, with offices in Austin, San Francisco, and Paris. We’re seeking a Staff Data Scientist to turn data across the platform into trusted insights, models, and decision systems that improve pricing, merchandising, personalization, and automation.

You will own data foundation and work closely with Product and Engineering to ship production-ready data products, while operating with ambiguity and high ownership.