Senior Applied Scientist, Customer Growth

A home is the biggest investment most people make, and yet, it doesn’t come with a manual. That's why we’re building the only app homeowners need to effortlessly manage their homes —  knowing what to do, when to do it, and who to hire. With Thumbtack, millions of people care for what matters most, and pros earn billions of dollars through our platform. And as one of the fastest-growing companies in a $600B+ industry — we must be doing something right. 

We are driven by a common goal and the deep satisfaction that comes from knowing our work supports local economies, helps small businesses grow, and brings homeowners peace of mind. We’re seeking people who continually put our purpose first: advocating for pros and customers, embracing change, and choosing teamwork every day.

At Thumbtack, we're creating a new era of home care. If making an impact and the chance to do good inspires you, join us. Imagine what we’ll build together. 

Thumbtack by the Numbers

• Available nationwide in every U.S. county
• Over 85 million projects started on Thumbtack
• More than 11 million 5-star reviews and counting
• Pros earn billions on our platform
• 1000+ employees 
• $3.2 billion valuation (June, 2021) 

About the Applied Science Team

We're looking for applied scientists with deep expertise in machine learning, optimization, building data products, and/or statistics. As part of a small product team you will have full ownership over your domain, so you should be a person who dreams big, then executes well.  

At Thumbtack, the Applied Science team is responsible for a wide variety of problems spanning machine learning, statistics, and computer science:

• Improve customer and service provider matching. Matching and optimization algorithms are fundamental to Thumbtack’s product: we now service millions of matches per week. Identifying better matches between customers and service providers has an incredible impact on the experience of customers and professionals transacting on our platform.
• Model complex relationships in the presence of many confounding factors. Predictive modeling problems are everywhere across our product. Our team works to scope, design and implement machine learning models to support Thumbtack’s product and marketing.
• Characterize marketplace dynamics. Thumbtack’s marketplaces consist of thousands of active markets across our service categories and U.S. cities. Via exploratory data analysis and experimental design, our team works to understand trends and behaviors within these markets.
• Build a healthy marketplace. We evolve and manage the monetization mechanics of our marketplace, including defining the parameters that affect the prices we charge.

Challenge

Our team is at the forefront of a massive amount of user data. We need to think a lot about both scaling as well as how to provide experiences for a wide set of users that we don’t necessarily know a ton about immediately. We are building experiences into our apps to onboard, engage, and re-engage our users and are constantly experimenting to produce delightful and consistent user experiences.

We are looking for someone with deep expertise in applying scientific techniques to marketplace growth and marketing problems. Our challenges include building systems to optimize our marketing spend to bring more customers to the marketplace, targeting our pro and customer acquisition efforts to ensure better outcomes for customers and pros and healthy marketplace growth, and building personalized experiences to engage and retain our customers and professionals.

Responsibilities

• Initiate and drive applied science initiatives to completion, with a focus on the business impact of those projects
• Architect and deploy machine learning systems to production
• Design and execute experiments, collect and analyze data to characterize our product and marketing
• Analyze a wide variety of data: structured and unstructured, observational and experimental
• Collaborate with engineering, marketing, and economists to use sound statistical practices
• Maintain the right balance between speed of execution and scientific rigor when designing solutions
• Technical mentorship of other applied scientists

What you'll need

If you don't think you meet all of the criteria below but still are interested in the job, please apply. Nobody checks every box, and we're looking for someone excited to join the team.

• Expert knowledge of machine learning techniques
• Ability to effectively read, write, and debug code in programming languages such as P