Senior Data Scientist, Experimentation & AI-Driven Insights

DataJobs; Austin (TX); On-site; USD 140,000 - 200,000; Full time

Benefits offered by this job

Medical coverage

13 paid holidays

Flexible time off

Volunteer time off

401(k) with match

Tuition reimbursement

Financial planning sessions

Student debt match

Snacks & beverages

Job summary

Realtor.com is seeking a Senior Data Scientist in Austin, TX to lead experimentation and analytics efforts from its headquarters. You will deliver data-informed product decisions, improve measurement, and build AI-enabled self-service reporting tools.

Responsibilities include owning experimentation, defining success metrics, and driving data quality across product initiatives, with cross-functional collaboration to uncover insights about consumer behavior and product performance.

Qualifications

• MS/BS in computer science, statistics, mathematics, operations research or related fields with 5 years of data science/analytics experience.
• Proficiency in SQL, Python, Tableau, and Amplitude.
• Experience with AI-enabled tools: Streamlit, Claude/MCP, n8n, Windsurf.

Responsibilities

• Lead experimentation and analytics workstreams across product and business analytics.
• Define success metrics and track data quality and measurement improvements.
• Design multivariate tests and translate results into actionable recommendations.
• Develop self-service AI-enabled reporting tools for cross-functional use.
• Identify opportunities to improve tracking and product performance through data insights.
• Communicate complex analyses to technical and non-technical stakeholders.

Education

MS/BS in CS/Statistics/OR

Tools

SQL

Python

Tableau

Amplitude

Streamlit

Claude/MCP

n8n

Windsurf

dbt

Airflow

Job description

Realtor.com is seeking a Senior Data Scientist in Austin, TX to lead experimentation and analytics efforts from its headquarters. You will deliver data-informed product decisions, improve measurement, and build AI-enabled self-service reporting tools.

Responsibilities include owning experimentation, defining success metrics, and driving data quality across product initiatives, with cross-functional collaboration to uncover insights about consumer behavior and product performance.