Data Scientist, Product Analytics

Realtor.com•Austin, TX

31d•Hybrid

About The Position

A Data Scientist in Product Analytics harnesses data to drive business growth by analyzing trends, applying advanced quantitative techniques, and advising on product roadmaps. This role involves collaborating with product teams to drive innovation and contributing insights that shape strategic decisions. It's an exciting opportunity for those passionate about combining data analysis with commercial acumen to influence and accelerate business success. Our team structure allows you to partner with senior leadership and present your findings to executives. If you're keen on learning product growth strategies, becoming a data expert, and pursuing your professional goals as you help grow an innovative real estate tech company, this work is for you. Join us as our newest Data Scientist, Product Analytics and help change the world of real estate, one home at a time.

Requirements

2+ years of related experience in analytics or data science.
Robust analytics skills including strong SQL experience and ability to work with and analyze large volumes of complex data.
Be a subject matter expert on measurement and statistical analyses for your stakeholders. Strong analytical thinking and ability to make data-driven decisions using statistical methods
Experience with data exploration and visualization tools like Tableau, Looker, Shiny, Streamlit
Comfort working in a collaborative, highly agile, intensely iterative environment
Four-year college or university degree in computer science, economics, statistics, mathematics, analytics, or a related discipline.

Nice To Haves

Prior experience with clickstream data or in product analytics, including using tools like Amplitude or Mixpanel
Expertise in applied experimentation and statistics concepts (e.g. confidence intervals, hypothesis testing, regression analysis, etc.)
Master's or PhD

Responsibilities

Business Performance Reporting, Visualization and Analysis: Be the primary partner for our cross-functional stakeholders to understand product performance across our consumer product funnels and search algorithms. When a metric is ahead or behind expectations, dig in to drive meaningful, actionable insights that help the business performance improve or double-down on success.
Deep-Dive Analysis: Use advanced techniques (A/B experimentation, statistical modeling, matched pair, and/or machine learning) to analyze consumer product performance at a lead and feature level. Create a rich understanding of how people are interacting with product features and use these insights to then make recommendations.
Opportunity Identification and Sizing: Both to set goals and help evaluate potential product enrichment opportunities, you will be tasked with forecasting and opportunity sizing. This will help our Product stakeholders understand the short-run and long-run dynamics of proposed changes to our product strategy, and create targets for driving business performance as well as optimize lead generation and funnel improvement opportunities.
Partnership and Communication: Partner closely with our Product stakeholders to identify and unlock opportunities, and with other data teams to improve platform capabilities around data architecture, data visualization, data modeling, and testing platforms.
Present your findings to the team and leadership with high visibility across the organization
Learn from the best and build on a cutting edge tech stack that allows for rapid skill development with AI.