Data Scientist

Thumbtack is a local services marketplace that connects customers who need to get things done with local, skilled professionals who can help. From plumbers and painters to DJs and personal trainers, Thumbtack helps millions of customers find the right professional for their project in over 1,000 categories.

We're looking for data scientists with deep expertise in statistics, machine learning, optimization, and/or building data products. Our process gives you full ownership over the projects you tackle, so you should be a person who dreams big, then executes well. At Thumbtack, the Data Science team is responsible for a wide variety of problems spanning statistics, machine learning, and computer science: * Characterize marketplace dynamics. Thumbtack’s marketplaces are comprised 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. * 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 pros 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.

* Design and execute experiments, collect and analyze data to characterize our product * Architect and deploy machine learning systems to production * Design and implement metrics that align with company goals * Analyze a wide variety of data: structured and unstructured, observational and experimental * Advise engineering and product teams on sound statistical practices

* M.S. or equivalent experience in Computer Science, Engineering, Statistics, or other relevant technical field * Expert knowledge of probability and statistics, including experimental design, predictive modeling, optimization, and causal inference * Familiarity with machine learning concepts: regression and classification, clustering, feature selection, curse of dimensionality, bias-variance tradeoff, neural networks, SVMs, etc. * Expert knowledge of a statistical language such as R or Python/pandas * Excellent written and verbal technical communication skills * Familiarity with a scripting language and/or shell scripting * Preferred: Ph.D. in Computer Science, Engineering or Statistics * Preferred: Experience with large-scale distributed systems * Preferred: Experience with tools in the Hadoop ecosystem such Hive, Pig, or Spark