Welcome to the Indeed Data Science Blog!
An Introduction to Indeed and Data Science at Indeed
About Indeed
Indeed is the #1 external source of hires in the US. If you don’t believe us, the plot below is a simple, if outdated, visualization. Our mission states that we “we help people get jobs”. This involves gathering all available jobs worldwide in one website, and helping job seekers navigate to the job of their choice. Try it out at indeed.com.
Indeed Data Science
Given the enormity of our data (many PBs), our website and product involve data science at its very core. This includes how we rank search results, estimate salaries for job listings, recommend positions and skills to job seekers, and provide tips to employers in crafting great job descriptions. The list continues and grows with each passing day.
Currently our Data Science organization consists of 30 data scientists and 10 product scientists. We’re based in four locations across the globe: Seattle, Austin, Tokyo and San Francisco. We embed directly in small high-velocity product/engineering teams across the company. Our role is to improve data quality, to promote the scientific method in decision-making, and to build better user-facing products with Indeed’s data.
If you’d like to learn more about our full-stack data science model, please see our recent “data to deployment” tech talk. The Indeed engineering blog contains more information on our engineering culture, software infrastructure, and how we use data to make decisions.
Why we created this blog and why you might enjoy reading it
We want to share our experiences. We’ve voraciously consumed blogs elsewhere (more on our favorites in a future post), and want to contribute to the conversation. This is partly motivated by our excitement to show off the cool things we’ve accomplished. Equally important: we want to give back to the community by exploring some of our missteps [blog]. Hopefully this helps you avoid the same pitfalls. We’ll also provide insight into our data science culture, including how and why we’ve decided to grow our organization.
Along the way, we’ll explain what motivated us personally to pursue this career path and the strategies we used to land that first job. In such a quickly evolving discipline, continuous learning is necessary. We’ll share what has and has not worked for us. We hope to make this blog useful to aspiring and practicing data scientists. We’ll solicit your suggestions, and promise to be frank and honest throughout. Hopefully, you’ll find these resources helpful in your career.
Blog topics
To provide an insight into data science at Indeed, we will publish articles on a variety of topics including:
- Why did we choose to be data scientists?
- How did we develop our careers?
- What exciting and novel technical advances have we made in (i) machine learning, (ii) statistics, (iii) data science infrastructure and (iv) scientific analysis?
- How have we built and structured the Indeed Data Science organization?
- What’s happening in the global job market today?
- Which problems have us stumped, and how are we planning to solve them?
- What public data sources are we creating?
- What is product science?
- How can product managers and software engineers collaborate effectively with data scientists?
- How do we conduct interviews and make hiring decisions?
- Full stack data science — what are the pros and cons?
- How do we use data science to build products?
- What strategies help in continuous development of data science skills on the job?
- How can data scientists evangelize their work to increase adoption and impact?
We hope you enjoy the content and look forward to your comments.
