Data Science Manager

Initial Responsibilities

• Manage the Digital Media and Lender (Mortgage) teams, focusing on optimizing digital media spend through predictive modeling, improving monetization strategies, and leveraging advanced experimentation techniques like multi-armed bandit models.

Potential for Growth

• You may have the opportunity to expand your scope to include the Marketing Data Science team, working on exciting challenges like consumer segmentation, media mix modeling, and personalization at scale. RDC loves to grow talent, and this role has clear pathways for leadership development.

• Be part of a respected and strategic analytics team that directly drives decisions, shapes strategy and influences the future of a platform with 100+ million unique monthly users.
• Benefit from solid executive sponsorship and support, providing your teams with the resources, guidance, and visibility needed to thrive and deliver transformative projects.
• Your work will drive real results in engagement, revenue growth, and innovation across sales, marketing, and product. High visibility, high impact—you’ll see your contributions make a difference.
• Collaborate with data science leaders across Realtor.com to bring innovative solutions to problems in digital advertising and customer experience.

• Take on a unique leadership role that blends strategic oversight with hands-on technical contributions. 💻
• Begin by managing two high-performing teams of 2-3 Staff/Senior Data Scientists, while actively engaging in pivotal projects.
• Ideal for someone who excels at mentoring talent and driving innovation. 🌟

Projects

• Data Science / Analytics Infrastructure: Partner with Engineering and Data Platform teams to build data layers and pipelines that enable DS/A work.

• Exploratory and Descriptive Analytics: Explore data and reveal patterns and trends, with insights into why we are seeing those patterns/trends.

• Predictive Modeling: Predict things like customer propensity, conversion likelihood, customer value, sales, future trends, etc.

• Other Data Science Modeling: Perform clustering analysis (e.g., customer segmentation), NLP (text analytics), and optimization.

• Experimentation: Conduct A/B testing in the context of marketing, monetization, product development, etc.

• Tracking & Reporting: Build automated tracking, reporting, and self-serve analytics tools (e.g., Tableau dashboards) to democratize data and insights within the company and enable fast activation of insights.

Tools & Stack

Utilize cutting-edge tools and technologies including Snowflake, Python, Tableau, Amplitude, Bayesian A/B testing, multi-armed bandit models, scalable machine learning, and ML Ops pipelines. Collaborate using cloud-based platforms like AWS and advanced visualization frameworks to deliver impactful results.

• Join a company with a data-driven culture where your insights are valued and championed by executive leadership.
• Work in vibrant hubs like Austin or Scottsdale, with a hybrid setup that balances your career ambitions and personal life. ✨
• Be part of a collaborative and innovative environment that values curiosity, teamwork, and high performance.

Who You Report To

• This role reports directly to Kevin Liu, our Director of Commercial Data Science & Analytics. Kevin reports to Ted Wroblewski, our VP Data Science and Analytics, and Ted reports to Vidya Krishnakumar, our SVP of Data Science and Analytics.

• Realtor.com’s Data Science & Analytics organization is strategically aligned under the CFO instead of our CTO.

Why It Matters

• RDC aligns data science with financial strategy to drive high-impact decisions that optimize revenue and growth. With this structure, you’ll not only gain visibility but also work closely with stakeholders across marketing, product, and digital media teams to influence decisions at the highest level.

Interview Process Length: The total process takes approximately 3.5 hours over 10 days.

Initial Chat: A 30-minute call with me. We'll discuss your background, aspirations, and answer all of your questions.

Hiring Manager Screen: A 30-minute session with Kevin Liu to explore your fit with the team and projects.

Technical Screening: A 45-minute session with a data science team member focusing on SQL, Python, and data modeling.

Virtual Onsite Interviews:
• Team Fit Meeting (30 minutes)
• SQL/Technical Assessment (45 minutes)
• Stakeholder Interaction (30 minutes)
• Final Check-In with Kevin Liu (15 minutes)

Offer & Onboarding: Following successful completion, we should be able to extend the offer in 3-5 business day.