Facebook Uses Kaggle to Recruit Top Data Science Talent
Company Size
1,000+
Country
- United States
Product
- Kaggle
Tech Stack
- Data Science
- Machine Learning
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Digital Expertise
- Employee Satisfaction
- Innovation Output
Technology Category
- Analytics & Modeling - Data Mining
- Analytics & Modeling - Machine Learning
Applicable Industries
- Professional Service
- Software
Applicable Functions
- Human Resources
- Product Research & Development
Services
- System Integration
- Training
About The Customer
Facebook, a leading global social media and technology company, has been at the forefront of innovation in various fields, including data science. With a vast user base and a plethora of data, Facebook constantly seeks top talent to drive its data-driven initiatives. The company’s HR team collaborates with Kaggle, a platform known for its data science competitions, to identify and recruit the best data scientists from around the world. By leveraging Kaggle’s community, Facebook aims to find candidates who possess not only technical skills but also creativity and tenacity.
The Challenge
In today’s competitive hiring environment, identifying and attracting the most qualified candidates is challenging even for top tech companies. Facebook has faced difficulties in finding data scientists with the right expertise and skills. Traditional hiring methods, such as resumes and interviews, often fall short in revealing the true capabilities of candidates. To address this, Facebook began running Kaggle competitions in 2012 as part of its data science recruiting strategy. These competitions are designed to attract a diverse pool of data scientists and test their skills in real-world scenarios.
The Solution
Facebook collaborates with Kaggle to design recruiting competitions tailored to specific job descriptions. These challenges are crafted to test the skills of job seekers and showcase the interesting problems they might tackle if hired. For instance, in its first recruiting challenge, Facebook sought data scientists with expertise in social network data, asking participants to predict missing links in a real-life social network. Another challenge involved making predictions about how a map of the entire Internet changes over time. A third competition focused on mining large text datasets, where participants were given over six million questions from StackExchange to predict keywords automatically. These competitions not only attract a large number of participants but also provide a platform for candidates to demonstrate their technical skills, creativity, and problem-solving abilities.
Operational Impact
Quantitative Benefit
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