Staff Data Scientist: AI-Driven Consumer Analytics Leader

Realtor.com; Austin (TX); On-site; USD 180,000 - 230,000; Full time

Benefits offered by this job

Inclusive medical coverage

13 paid holidays

Flexible Time Off

Tuition Reimbursement

401(k) with company match

Job summary

Realtor.com® in Austin seeks a Staff Data Scientist to lead measurement and analytics across consumer product experiences—spanning content, search, visualization, and personalization. You’ll own the most ambiguous, high-visibility problems end-to-end while setting the technical bar and mentoring other data scientists on the team.

You’ll partner with Product, Engineering, and leadership to define what gets measured, shape experimentation roadmaps, and say no to low-value ad hoc requests in favor

Qualifications

• 8+ years of experience in data science, applied statistics, or machine learning with a quantitative degree.
• Experience owning ambiguous, high-visibility analytical initiatives end-to-end.
• Strong experimentation fundamentals—A/B testing, power analysis, and causal inference.
• Experience mentoring or leading other data scientists or analysts.

Responsibilities

• Own high-visibility cross-team analytics initiatives end-to-end.
• Set analytics standards for test-and-learn frameworks and causal inference approaches.
• Partner with Product and Engineering to shape measurement roadmaps for consumer initiatives.
• Mentor data scientists and elevate rigor across the team.
• Translate analytical findings into clear recommendations for technical and executive audiences.

Skills

SQL & Python

Analytics tooling

Mentoring

Communication

AI-native workflows

ETL pipelines

Education

Bachelor's in CS/Statistics/Math/OR

Master's in quantitative field

PhD (preferred)

Tools

dbt

Airflow

Snowflake

Tableau

Langfuse

Job description

Realtor.com® in Austin seeks a Staff Data Scientist to lead measurement and analytics across consumer product experiences—spanning content, search, visualization, and personalization. You’ll own the most ambiguous, high-visibility problems end-to-end while setting the technical bar and mentoring other data scientists on the team.

You’ll partner with Product, Engineering, and leadership to define what gets measured, shape experimentation roadmaps, and say no to low-value ad hoc requests in favor