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Data Scientist, Product Analytics

San Francisco, CA

ABOUT RETOOL

Nearly every company in the world runs on custom software: Gartner estimates that up to 50% of all code is written for internal use. This is the operational software for refunding orders, underwriting loans, onboarding employees, analyzing transactions, and providing customer support. But most companies don’t have adequate resources to properly invest in these tools, leading to a lot of old and clunky internal software or, even worse, users still stuck in manual and spreadsheet flows. 

At Retool, we’re on a mission to bring good software to everyone. We’re building a new type of development platform that combines the benefits of traditional software development with a drag-and-drop UI editor and AI, making it dramatically faster to build internal tools. We believe that the future of software development lies in abstracting away the tedious and repetitive tasks developers waste time on, while creating reusable components that act as a force multiplier for future developers and projects. The result is not just productivity, but good software by default. And that’s a mission worth striving for. 

Today, our customers span from small startups building their first operational tools to Fortune 500 companies building mission-critical apps for thousands of users across their business. Interested in joining us? Let us know! 

WHY WE'RE LOOKING FOR YOU

Retool started as a way to address obstacles with internal tools and has grown into a company that solves internal tooling for thousands of companies (big and small). As Retool’s product and user base evolves, we’ve found ourselves with numerous opportunities to leverage data-driven insights to influence product development.

To continue our fast-paced growth, we must build a world-class data science and analytics team to deliver strategic product insights. You’ll help us get there by defining key metrics and developing data-driven insights to maximize impact. We're looking for someone ready to get their hands dirty, motivated by impacting the business, and constantly curious.  This is the right role for someone who thrives while making sense of the blurry space that is data at a high-growth startup.

WHAT YOU'LL DO

As a member of the data science analytics team, you’ll play a pivotal role in building the data culture at Retool. You’ll initiate projects to generate strategic insights and help the company remain data-driven. You’ll build data pipelines, dashboards, and reports to streamline operations, inform strategic priorities, and empower stakeholders to make data-informed decisions. You’ll apply statistical knowledge and the scientific method to the data questions we face today, and help us think critically about the questions of tomorrow.

WHO YOU'LL WORK WITH

As a data scientist, you’ll work closely with engineering, design, and product teams to size opportunities, prioritize product features, set goals, and quantify impact. We’re a hard-working, passionate bunch who are motivated by collaboration, strong results, and bringing the impact of Retool to our customers. When we’re in the office, we enjoy eating lunch (and occasionally dinner!) together, and we’ve been known for our lively game nights. But at the root of it all, we come together to show our customers and not-quite-yet customers how Retool can make them and their companies more efficient and successful. If this sounds like a fit, we’d love to hear from you! 

THE SKILLSET YOU'LL BRING:

  • 4+ years of experience working in data science and/or product analytics, ideally at a high-growth enterprise SaaS business
  • Experience defining and implementing product metrics
  • Expertise in leveraging data to deliver actionable insights for non-technical stakeholders
  • Skilled at data visualization, with strong opinions on the right way to distill information to various audiences
  • Strong SQL and data modeling skills, with experience applying skills to create data models thoughtfully in a warehouse environment
  • Proficiency in statistical analysis (e.g., descriptive statistics)
  • A bias towards communication and collaboration with business and technical stakeholders
  • Experience bolstering quantitative analysis with qualitative insights
  • A solution-oriented growth mindset. You’ll need to be a self-starter and thrive in a dynamic environment
  • Comfortable with common git workflows and at least one scripting or statistical programming language (ideally Python and/or R)

IN THIS ROLE, YOU'LL:

  • Embed with engineering, product, and design teams to surface key insights
  • Develop dashboards and define metrics that drive key product and business decisions 
  • Build and maintain ETL pipelines
  • Work with our engineering teams to validate existing data sources, identify opportunities to improve data quality, and craft requirements for robust new instrumentation as needed
  • Be a self-starter

For candidates based in San Francisco, the pay range(s) for this role is listed below and represents base salary range for non-commissionable roles or on-target earnings (OTE) for commissionable roles. This salary range may be inclusive of several career levels at Retool and will be narrowed during the interview process based on a number of factors such as (but not limited to), scope and responsibilities, the candidate’s experience and qualifications, and location. 

Additional compensation in the form(s) of equity, and/or commission/bonuses are dependent on the position offered. Retool provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.

San Francisco

$154,500 - $209,100 USD

Retool offers generous benefits to all employees and hybrid work location. For more information, please visit the benefits and perks section of our careers page!

Retool is currently set up to employ all roles in the US and specific roles in the UK. To find roles that can be employed in the UK, please refer to our careers page and review the indicated locations.

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