Ref#: R0019307

Our mission.

As the world’s number 1 job site, our mission is to help people get jobs. We need talented, passionate people working together to make this happen. We are looking to grow our teams with people who share our energy and enthusiasm for creating the best experience for job seekers.

The team.

We are a rapidly growing and focused product team building the most popular job site on the planet. Every month, over 250 million people count on Indeed to help them find jobs, make it easy to apply, research companies, and connect qualified candidates to their job openings. With product teams in Austin, Tokyo, Seattle, San Francisco, Singapore and Hyderabad, we are improving people's lives all around the world, one job at a time.

The base salary range below represents the low and high end of the Indeed salary range for this position. Actual salaries will vary and may be above or below the range based on various factors including but not limited to location, experience, and performance. The range listed is just one component of Indeed's total compensation package for employees. Other rewards include quarterly bonuses, Long Term Incentive Plan units, an open Paid Time Off policy, and many region-specific benefits. 

Austin Base Salary Range: 110,000 - 143,000 USD per year

Your job.

This position will be part of Indeed’s Analytics Tools experimentation team and will be located in Austin where the team needs a presence to better support users of experimentation and other analytical products.

  • You will own multiple data indices that are using to analyze experimentation and user interactions on the Indeed websites.

  • Be the index owner decide what information contained in the index should be added, removed or modified

  • Review and act on external requests for modifications to the index(es).

  • Increase general usage of experimentation at Indeed by advocating best practices and becoming an evangelist for how to use experimentation for optimal results.

  • Create and maintain training content best practice use of indexed data and corresponding tools

  • Build communities around experimentation.

  • Work directly with teams to create an onboarding process that optimizes the teams’ use of existing experimentation products.

  • Proactively identify areas where using logging analysis tools can have a positive impact.

  • Perform gap-analysis to identify work required to get new teams onboarded to experimentation.

  • Work with data pipeline engineering team to product manage the entire data funnel from event to appearance as metric in experimentation report.

  • Support broader use of experimentation for other products such as email, model based tests and other areas with limited TS support.

  • Manage tools used for analysis of universal logged data - these tools are both internal and provided by 3rd party vendors.

  • Own universal logging for data that is currently sent to third party applications.

About you.

You're someone who wants to see the impact of your work making a difference every day. Your friends describe you as thorough, analytical and detail-oriented. You are someone with high standards who leads by example, and who will take pride in Indeed like we do. 

You’ve got a technical background and you understand how software development teams work, and how engineers think. Most of all, you love solving hard technical challenges to make a difference in the lives of other people, whether they be job seekers, employers or your fellow Indeedians. 


  • Bachelor's Degree in Computer Science, Statistics, Electrical Engineering or a closely related field, or equivalent experience.
  • 2+ years of product management experience in a data driven environment.
  • Experience with large scale databases and query languages
  • Background working with on-prem, cloud-based, and hybrid data infrastructure
  • Ability to drive, contribute to, and communicate solutions to technical product challenges.
  • Ability to roll-up your sleeves and work in process or resource gaps and fill it in yourself.
  • Outstanding data analysis and data-driven decision making skills.
  • Experience making complex data-driven business decisions.
  • Experience collaborating with large cross-functional teams.
  • Excellent written and oral communication skills in English.

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