LegalZoom Careers

Description

About LegalZoom

As the industry leader for over 20 years, innovation remains at the center of all we do. We're creative thinkers and problem solvers with a passion for building legal and tax products that make a positive impact on the world, and we're always looking for exceptional people to push us further. 

At LegalZoom.com, Inc. we have transformed the legal industry with the launch of our cloud-based services and groundbreaking technology. Millions of customers have counted on us to officially start and run businesses, protect brands and intellectual property, and look after loved ones through wills and trusts. We're here to make legal help accessible to all. 

With us, you'll do work that's as rewarding as it is challenging with a team where every voice matters and diversity, equality, and inclusion are truly embraced. Together, we'll continue to democratize the law and make a real difference in the lives of millions.

Remote-first

Since March 2020, our Zoomers have worked remotely and reported an overall better work-life balance with more time for family and personal wellness.

At the end of 2021, LegalZoom made the official commitment to being a remote-first company. Remote-first means that there is no expectation that Zoomers come into an office for a fixed number of days outside of those employees identified as essential onsite workers. While we remain a remote-first culture, our local offices have evolved as collaboration spaces for Zoomers to meet and engage in person.

Overview

The Data Science team at LegalZoom helps us make measurably better decisions faster. We work on everything from shaping product strategy to designing and running experiments that let us know how well our strategy performs. 

As a Data Scientist on our Product Data Science team, you’ll tackle many of our business's existential questions. We work on questions around go-to-market & commercialization strategy, modeling customer lifetime value, and digging into the details of how our customers interact with our products.

You will

• Be a key driver of product strategy by thinking beyond immediate analysis and understanding the long-term implications of actions
• Perform descriptive and predictive analyses to form hypotheses about how we can grow the business through building better products
• Influence LegalZoom leadership to pursue our hypotheses so that we better serve customers and grow our business 
• Design and run experiments to test our hypotheses, including defining metrics that enable us to understand product experience
• Interpret experiment results and use them to drive strategic and tactical recommendations for how to improve our products 
• Provide insights at scale through building pipelines and dashboards to provide a more complete view of our products 
• Work closely with Product and Engineering partners to help them understand the data and form their own hypotheses so we can move faster 
• Explore, automate, and leverage our data in analyses that will shape Legalzoom products
• Work with fellow data scientists to continually improve our code and data best practices, prioritizing long-term data hygiene

You have

• Basic qualifications: M.S. or Bachelors degree in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative fields 
• (If M.S. degree, a minimum of 1+ years of industry experience required and if Bachelor's degree, a minimum of 2+ years of industry experience as a Data Scientist or equivalent)
• 3+ years of tech industry experience; subscriptions or logistics services preferred
• Advanced SQL expertise
• Understanding of experimental design (e.g. A/B experiments) and statistical methods (e.g. Bayesian inference)
• Ability and experience in extracting insights from data, and summarizing learnings / takeaways
• Product data science or consulting experience
• Advanced experimentation experience including multivariate and causal analysis
• Experience working on web analytics (behavioral analytics)
• Detailed knowledge of data warehouse technical architecture, infrastructure components, ETL, and reporting/analytic tools and environments
• Solid understanding of source data, its strengths, weaknesses, semantics, and formats; solid knowledge of logical and physical data modeling concepts (relational and dimensional)
• Someone who is willing to contribute new ideas and articulate them to a variety of business partners and not just execute on existing ones