Homeward

Senior Data Scientist

April 19, 2022

Anywhere

About Homeward Buying a home should be an exciting milestone. But all too often, it’s stressful, especially in a competitive market or when you’re buying and selling at the same time. So we’re redesigning the home-buying experience. We’re a fast-paced real estate startup that empowers agents to help homebuyers buy with cash. We buy homes on behalf of our partners’ clients with our cash, then the client buys the home back from us.  Founder and CEO Tim Heyl, a 10-year industry veteran and owner of one of the fastest-growing agent teams in the country, started Homeward in 2018. In fact, he bought our first customer’s home with his own life savings. Today we offer two services — Buy with cash and Buy before you sell —  in Texas, Colorado, and Georgia. We’ve raised more than $160MM in equity capital from top-tier venture investors, including Norwest, Blackstone Alternative Asset Management, Adams Street, Javelin, and LiveOak. Our leadership team includes experts from the real estate, mortgage, and technology industries.   About the Role We're seeking a Senior Data Scientist to help us build a simpler, more customer-centric experience in partnership with real estate agents.  Data at Homeward is a crucial part of our mission to streamline the home buying and selling process.  From dimensional modeling and pipelines to machine learning products and decision support, data science at Homeward is a diverse role with many opportunities to positively impact our success.  This position is not eligible for visa sponsorship.   Responsibilities: Partner with data engineering and analytics teams to drive data-driven decision making throughout the business and define the data models required to support it Proactively identify and champion projects that solve complex problems across multiple domains Work with product managers and analysts to design and build solutions that fulfill operational and reporting needs throughout the company. Design, train, and implement machine learning algorithms to automate or augment human decision making and business processes Leverage predictive models to optimize customer experiences Define and advance best practices within data science and product teams Requirements: 5+ years experience working on a small, tight-knit, high-performing data team, or 3+ years plus a PhD in a related STEM field Advanced statistical knowledge, and the ability to gather insights and influence decision-making using data Advanced working knowledge of SQL and database structure and modeling Experience with Python and software engineering fundamentals Experience launching productionized machine learning models at scale Prefer experience with cloud-based PaaS and IaaS offerings (most notably AWS) Ideally, familiarity with data in the real estate domain (i.e. MLS data)   Values Golden Rule “Treat others how you want to be treated.” We’re building our company culture and customer experience with this as the guiding principle. It’s a simple rule, but emphasizes that we  don’t prioritize money or growth over people.  Calm Focus We don’t chase every opportunity and rush from urgent task to urgent task. We relax, stay calm, and focus on our company-wide objectives. If something is out of scope, we say “no”. If something feels rushed we slow down and think it through so we can avoid unnecessary rework later.  We don’t bombard each other with notifications expecting instant response times. We block off time for deep work so we can get into the flow and create solutions our customers love. Multi-tasking isn’t effective or enjoyable.   Cross Functional Collaboration We look at our customers’ experience holistically and recognize that improving it requires support from multiple functions. Given this, we’re excellent collaborators. No function is more important than another and we’re eager to work as a team to solve our customers’ toughest problems. We value strong internal alignment, and take pride in understanding and considering our  teammates' perspectives before expressing our own.

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