Staff Data Scientist - Lead Intelligence

Description

Recognized as the No. 1 site trusted by real estate professionals, Realtor.com® has been at the forefront of online real estate for over 25 years, connecting buyers, sellers, and renters with trusted insights and expert guidance to find their perfect home. Through its robust suite of tools, Realtor.com® not only makes a significant impact on the real estate industry at large, but for consumers, navigating the biggest purchase they will make in their life, by providing a user experience that is easy to use, easy to understand, and most of all, easy to make decisions.

Join us on our mission to empower more people to find their way home by breaking barriers to entry, making the right connections, and building confidence through expert guidance.

About the Role:

The Data Science & Analytics organization at Realtor.com is looking for a Staff Data Scientist to build the scoring and optimization engine behind Lead Intelligence & Revenue Optimization.

This is a revenue management problem at national scale. Our inventory is consumer intent, and every lead is a perishable unit of it. You will determine what each lead is worth, who it should go to, and how the full supply should be distributed across clients, products, and geographies to maximize revenue. That means scoring likelihood to transact, valuing inventory by geography and intent signal, and solving allocation and distribution as an optimization problem rather than a set of static rules.

The constraints are real: product eligibility, client commitments, and the experience of both the consumer and the client. The signal is noisy and arrives continuously. You will define the objective function, build the models that feed it, and work with Engineering to put the results into production decisioning.

You will work at the intersection of lead quality and revenue outcomes, partnering with Product, Marketing, Pricing, Finance, Tech, and Client Engineering to turn models into automated decisions across the Realtor.com ecosystem.

Top Reasons to Apply:

• High-Impact Marketplace Optimization: You will directly influence revenue routing and inventory allocation strategies across a massive, national two-sided marketplace.
• Operations Research Applied to Revenue: Formulate and solve the valuation and allocation problems that determine what each lead is worth and where it earns the most, with pricing as a direct partner at the table.
• Full Ownership of Next-Gen Data Layers: Take full ownership of our predictive close models and Lead-To-Transact pipeline, and set the standard for how these models are built, validated, and deployed.
• Complex Data Problem Solving: Uncover non-obvious revenue streams, such as identifying low-priority land-listing leads that actually convert into high-value single-family home transactions.
• Direct Stakeholder & Executive Visibility: Partner directly with Product, Tech, Pricing, Marketing, and Engineering, and bring your results and tradeoffs to VP and SVP audiences who act on them.
• Scale and Consequence: Work with clickstream, lead, and transaction data across a national marketplace, where the decisions your models make are measured in revenue and in client outcomes.

What You'll Do:

• Lead Quality & Scoring: Own and advance the predictive close models that score likelihood to transact, as part of the Lead-To-Transact pipeline, so that the leads we deliver generate revenue for the clients who pay us for them. Extend scoring beyond conversion to the expected value of a lead.
• Inventory Valuation: Build the models that value lead inventory by geography, product, and intent signal, and establish that valuation as the common currency for allocation, distribution, and pricing decisions.
• Allocation & Distribution Optimization: Formulate lead distribution as a constrained optimization problem across clients, products, and geographies, using methods such as mixed-integer programming and stochastic optimization, and move the business from rules-based allocation toward optimized allocation.
• Price and Inventory Together: Partner with Strategic Pricing to model how price and inventory interact, including price elasticity and willingness-to-pay, so that allocation and pricing decisions are solved against the same revenue objective.
• Demand and Supply Alignment: Work with the teams that own demand forecasting and marketing acquisition, contributing lead valuation and conversion insight by market so that supply is acquired and committed against where it is worth the most. Perform scenario analysis to maximize outcomes while optimizing the consumer and client experience.
• Impact Simulation: Simulate and report on the knock-on effects of changes to product eligibility, allocation rules, and price across various business units before they are implemented.
• Experimentation: Design and analyze experiments and structured test-and-learn programs to validate scoring models and allocation logic in market, and establish statistical best practices for the function.
• Production and Adoption: Work with Tech and Client Engineering to take models from development into production decisioning, ensure the standardized implementation of rules across the Realtor.com ecosystem, and monitor performance after launch.
• KPI Development & Monitoring: Build and track the KPIs that measure lead quality, delivery, and revenue yield, and build the dashboards that make them self-service for stakeholders.
• Communication: Translate complex statistical and optimization results into clear narratives, assumptions, and tradeoffs for business and executive audiences, and document methodologies through reproducible code.

What You'll Bring:

• Education & Experience: 8+ years of experience in data science, applied statistics, or machine learning and a Bachelor’s degree (or equivalent experience) in computer science, statistics, mathematics, operations research, or a related quantitative field. (6+ years with a Master's, 3+ years with a Ph.D.)
• Optimization Mindset: Demonstrated experience formulating business problems as constrained optimization problems and delivering solutions with measurable revenue or margin impact. This is the core of the role.
• Inventory and Allocation:  2+ years of inventory optimization, allocation, or capacity and revenue management experience, ideally in a digital marketplace, SaaS, or another industry with perishable inventory.
• Predictive Modeling: Experience building models that score likelihood of an outcome such as purchase, conversion, or churn, and validating them against realized results.
• Technical Mastery: Advanced SQL required. Python proficiency (pandas, numpy, scipy) with 4+ years, and hands-on experience with optimization solvers such as Gurobi, CPLEX, OR-Tools, or Pyomo.
• Analytical Rigor: Strong understanding of experimentation and statistics (hypothesis testing, regression analysis, power analysis, causal inference, statistical modeling) and of modeling and simulation.
• From Model to Production: Experience moving models out of development and into systems that make decisions, and measuring the business impact once they are live.
• Cloud Platforms: Experience working within cloud-based environments such as AWS and Snowflake.
• Data Visualization: Experience with tools like Tableau, Shiny, or Streamlit to create impactful data stories for executive stakeholders.
• Strategic Thinking: 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.
• Agility: Comfort working in a highly agile, intensely iterative environment where you must manage multiple priorities and ambiguous concepts.

Preferred Qualifications

• Ph.D. in Operations Research or Industrial Engineering
• Revenue management experience combining inventory and pricing, including price segmentation, price optimization, or dynamic pricing, in sectors such as hospitality, transportation, travel, or retail
• Forecasting experience at scale, including forecasts by geography, using time series, machine learning, or Bayesian methods
• Marketplace or property tech revenue analytics, lead generation, or CRM/Salesforce expertise

How We Work:

We balance creativity and innovation on a foundation of in-person collaboration. For most roles, our employees work four or more days in our offices, where they have the opportunity to collaborate in-person, adding richness to our culture and knitting us closer together.

How We Reward You:

Realtor.com is committed to investing in the health and wellbeing of our employees and their families. Our benefits programs include, but are not limited to:

• Inclusive and Competitive medical, Rx, dental, and vision coverage
• Family forming benefits
• 13 Paid Holidays
• Flexible Time Off
• 8 hours of paid Volunteer Time off
• Immediate eligibility into Company 401(k) plan with 3.5% company match
• Tuition Reimbursement program for degreed and non-degreed programs
• 1:1 personalized Financial Planning Sessions
• Student Debt Retirement Savings Match program
• Free snacks and refreshments in each office location
• Do the best work of your life at Realtor.com

Here, you’ll partner with a diverse team of experts as you use leading-edge tech to empower everyone to meet a crucial goal: finding their way home. And you’ll find your way home too. At Realtor.com®, you’ll bring your full self to work as you innovate with speed, serve our consumers, and champion your teammates. In return, we’ll provide you with a warm, welcoming, and inclusive culture; intellectual challenges; and the development opportunities you need to grow.

Diversity is important to us, therefore, Realtor.com® is an Equal Opportunity Employer regardless of age, color, national origin, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, marital status, status as a disabled veteran and/or veteran of the Vietnam Era or any other characteristic protected by federal, state or local law. In addition, Realtor.com® will provide reasonable accommodations for otherwise qualified disabled individuals.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.