Want an interview at Facebook? Facebook will review the top entries in the competition and offer you an interview if they like what they see. This is your opportunity to demonstrate your skills on a real-world social network dataset, and show them your creativity, open-mindedness and tenacity in the face of an open-ended predictive modeling problem.
The challenge is to recommend missing links in a social network. Participants will be presented with an external anonymized, directed social graph (no, not Facebook, keep guessing) from which some edges have been deleted, and asked to make ranked predictions for each user in the test set of which other users they would want to follow.
Eligibility
You must compete as an individual in recruiting competitions. You may only use the data provided to make your predictions. Facebook will review the code of the top participants before deciding whether to offer an interview.
Requirements
- M.S. or Ph.D. in a relevant technical field, or 4+ years experience in a relevant role
- Extensive experience solving analytical problems using quantitative approaches
- Comfort manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources
- A strong passion for empirical research and for answering hard questions with data
- A flexible analytic approach that allows for results at varying levels of precision
- Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner
- Fluency with at least one scripting language such as Python or PHP
- Familiarity with relational databases and SQL
- Expert knowledge of an analysis tool such as R, Matlab, or SAS
- Experience working with large data sets, experience working with distributed computing tools a plus (Map/Reduce, Hadoop, Hive, etc.)
Prize
The main prize is interview at Facebook and possibility for job position. Facebook is seeking Data Scientists to join their Data Science team. Individuals in this role are expected to be comfortable working as a software engineer and a quantitative researcher. The ideal candidate will have a keen interest in the study of an online social network, and a passion for identifying and answering questions that help us build the best products.
- Work closely with a product engineering team to identify and answer important product questions
- Answer product questions by using appropriate statistical techniques on available data
- Communicate findings to product managers and engineers
- Drive the collection of new data and the refinement of existing data sources
- Analyze and interpret the results of product experiments
- Develop best practices for instrumentation and experimentation and communicate those to product engineering teams
Application
test.csv contains a list of nodes in the social graph. For each node, recommend up to 10 other nodes for that user to follow.
Submit a 2-column csv file. The first column (source_node) should contain an integer representing the nodes in test.csv, in the same order that they appeared in test.csv. The second column (destination_nodes) should contain a space-delimited series of between 0 and 10 integers, representing the 10 recommended nodes.
