Facebook Data Scientist, Population and Survey Sciences in Menlo Park, California
Facebook's mission is to give people the power to share, and make the world more open and connected. Through our growing family of apps and services, we're building a different kind of company that helps billions of people around the world connect and share what matters most to them. Whether we're creating new products or helping a small business expand its reach, people at Facebook are builders at heart. Our global teams are constantly iterating, solving problems, and working together to make the world more open and accessible. Connecting the world takes every one of us—and we're just getting started.
We’re looking for data scientists to work on our internal survey, user feedback, and sentiment measurement systems that empower our users to have a voice in Facebook’s development every day. As a key member our Population and Survey Sciences team, you will play a leading role in providing innovative and methodologically rigorous research across the company to understand user attitudes and sentiment. With more than a million survey responses daily, your primary focus will be to differentiate the signal from the noise and provide teams with the information and insights they need to make better, more informed product decisions. You will enjoy working with one of the richest data sets in the world to combine attitudinal and behavioral measures to develop sustainable solutions to nagging survey-related methods and data problems.
The perfect candidate will have a background in a quantitative or technical field, will have experience working with large data sets and relational databases, and will have some experience in data-driven decision making. You are focused on results, a self-starter, and have superior computational, analytical and communication skills. This position is based full time in our Menlo Park, CA office.
- Apply your expertise in quantitative analysis and data mining to proactively and continuously monitor the overall quantitative user sentiment ecosystem.
Exploratory and diagnostic analyses to identify changes to response rates, demographic shifts, and changes in user sentiment.
Build key data sets to empower operational and exploratory analyses to look for new patterns in user sentiment and relationships with Facebook experiences.
Generate and test hypotheses to identify root causes of trend changes.
Partner with Engineering teams to ensure the reliability and sustainability of survey data collection on the Facebook platform.
Spread best practices for measuring user attitudes and sentiment
Sampling and bias correction
Use of tools and infrastructure
Automate analyses, build dashboards and author pipelines via SQL and python based ETL framework
2+ years experience doing quantitative analysis
BA/BS in Computer Science, Economics, Math, Physics, Statistics or other quantitative field.
Experience in SQL or other programming languages or working with relational databases
Development experience in any scripting language (PHP, Python, Perl, etc.)
Understanding of statistics (e.g., hypothesis testing, regressions).
Experience manipulating data sets through statistical software (ex. R, SAS) or other methods.
Experience with the statistical design and analysis of surveys (e.g., sampling, non-response analysis and bias correction).
Experience with distributed computing (Hive/Hadoop).
Experience with Natural Language Processing (NLP) or text analysis.
Familiarity with survey research methods.
Equal Opportunity: As part of our dedication to the diversity of our workforce, Facebook is committed to Equal Employment Opportunity without regard for race, color, national origin, ethnicity, gender, protected veteran status, disability, sexual orientation, gender identity, or religion. We are also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at firstname.lastname@example.org or you may call us at 1+650-308-7837.