Senior Pricing Strategy Analyst

Realtor.com Careers•Austin, TX

9h•Hybrid

About The Position

The Data Science & Analytics organization at Realtor.com is looking for a Senior Pricing Strategy Analyst to join our team as a strategic partner supporting Lead Intelligence & Revenue Optimization. This role will provide strategic insights and data driven guidance to support the creation of a unified engine that strategically supports the full lifecycle of a lead—optimizing lead generation and inventory allocation to maximize organizational yield and client satisfaction. As a Senior Data Analyst, you will not just report data; you will be a key analytical engine driving our revenue management strategy. You will work at the intersection of supply quality and demand yield, using data to drive precise decisioning for geo-targeted marketing and smart inventory management. Top Reasons to Apply Massive White Space & High Visibility: Over the past year, Realtor.com has successfully stood up a brand-new Pricing Organization. We’ve built the data foundation; now, we are in Phase 2—hardening the function and scaling it out. If you love being in the spotlight and want a massive say in shaping a critical business function from the ground up, this is your stage. Highly Valued Executive Investment: This team isn't tucked away in a back room—it is one of the most heavily backed, highly valued investment areas within the company. You will have a front-row seat to a significant roadmap of strategic initiatives, giving your work direct, measurable airtime with executive leadership. Move Beyond the Dashboards: We aren't looking for someone to maintain Power BI dashboards or pull passive data tickets. We already have talented data scientists and analysts. We need a commercially minded strategist who can look at pricing mechanics, understand market dynamics, and drive actual revenue strategy.

Requirements

Bachelor's Degree in Business Analytics, Math, Economics, or a related field, with 5+ years of experience analyzing data to answer critical business questions. Master’s Degree with 3+ years of experience or PhD also eligible.
Advanced knowledge of SQL is required.
Proficiency in Python or R is a plus for building sophisticated optimization models.
Experience with tools like Tableau, Shiny, or Streamlit to create impactful data stories for executive stakeholders.
Strong understanding of experimentation and statistics (e.g., hypothesis testing, regression analysis, and statistical modeling) to analyze lead and feature-level performance.
Experience with modeling and simulation capabilities preferred.
Experience working within cloud-based environments such as AWS and Snowflake.
Ability to handle operational complexity and move from "what" the data says to "why" it is moving, enabling data-driven decisioning for the entire organization.
Comfort working in a highly agile, intensely iterative environment where you must manage multiple priorities and ambiguous concepts.

Responsibilities

Lead Intelligence Strategy & Support: Act as the primary analytical partner for the Lead Intelligence initiative, helping to define and align lead inventory allocation and optimization across all geographies.
Advanced Forecasting & Modeling: Evolve and improve sophisticated forecasting models for lead delivery and sales pipeline. You will perform scenario analysis to maximize outcomes while optimizing the consumer and client experience.
Inventory & Yield Optimization : Conduct deep-dive analyses to identify and prioritize high-value leads by geography and intent signal. Use these insights to recommend rules-based allocation strategies that optimize yield.
Impact Simulation: Simulate and report on the knock-on effects of changes to product eligibility and allocation rules across various business units.
KPI Development & Monitoring: Track and forecast lead delivery for operational planning, building new KPIs to measure the success of lead outcomes and revenue optimization.
Cross-Functional Partnership: Collaborate with Product, Tech, Pricing, and Client Engineering teams to ensure the standardized implementation of rules across the RDC ecosystem.