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 highly capable engineering team building the most popular job site on the planet. Every month, over 200 million people count on us to help them find jobs, publish their resumes, process their job applications, and connect them to qualified candidates for their job openings. With engineering hubs in Seattle, San Francisco, Austin, Tokyo and Hyderabad, we are improving people's lives all around the world, one job at a time.
Product Science advances data-driven decision-making using the scientific method on Indeed’s products. In the Data Science organization, the Product Science Manager and Product Scientists are embedded working closely with Product Managers and their Engineering teams. Both Product Scientists and Product Science Managers are a mixture of a statistician, scientist, machine learning expert, and engineer. Product Science Managers maintain the overall vision and specific purposes of the embedded Product Scientist leading the team to achieve maximum impact.
While our Data Scientists largely focus on production machine learning, ML is just one tool in a Product Scientist’s toolbox. Product Scientists use a variety of technical and interpersonal skills with the goal of driving business impact using whatever tools necessary. Typical tasks can range from designing better surveys and A/B tests to building full-service machine learning models while working with product managers and engineering teams to ensure utilization and impact.
You understand that the best managers serve their teams by removing roadblocks and giving individual contributors autonomy and ownership. You have high standards and will take pride in Indeed and push teammates to be better. You have delivered challenging technical solutions at scale. You have led Data Science or Engineering teams, and earned the respect of talented practitioners. You are equally happy talking about deep learning and statistical inference, as you are brainstorming about practical experimental design and technology career development. You love being in the mix technically while providing leadership to your teams.
- Significant prior success as a Data, Product, or Decision Scientist working on challenging problems at scale
- Advanced coursework in statistics, machine learning, programming, or related skills
- 3+ years of industry experience, with expertise in statistical modeling and/ or machine learning
- The ability to guide a team to achieve important goals together
- Have full stack experience in data collection, aggregation, analysis, visualization, productionization, and monitoring
- Strong desire to solve tough problems with scientific rigor at scale
- An understanding of the value derived from getting results early and iterating
- Ability to write and present results to both technical and non-technical audiences
- Strong ability to coach Product Scientists, helping them improve their skills and grow their careers
- Preferred Ph.D. or M.S. in a quantitative field such as Computer Science, Natural Science, Operations Research, Statistics, Econometrics or Mathematics
- Passion to answer Product and Engineering questions with data
We get excited about candidates who can
- Program in R, Python, and/or Java
- Fish for data using SQL and/or Pandas
- Communicate concisely and persuasively with engineers and product managers
Indeed provides a variety of benefits that help us focus on our mission of helping people get jobs.
View our bounty of perks: http://indeedhi.re/IndeedBenefits
Indeed is proud to be an equal opportunity employer, seeking to create a welcoming and diverse environment.
All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.