Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps and services like Messenger, Instagram, WhatsApp, and Novi further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. To apply, click “Apply to Job” online on this web page.
Research Data Scientist Responsibilities:
1. Build pragmatic, scalable, and statistically rigorous solutions to large-scale web, mobile and data infrastructure problems by leveraging or developing state-of-the-art statistical and machine learning methodologies on top of Meta’s unparalleled data infrastructure
2. Work cross-functionally to define problem statements, collect data, build analytical models and make recommendations
3. Build and maintain data driven optimization models, experiments, forecasting algorithms, and machine learning models
4. Leverage tools like Python, R, Hadoop, and SQL to drive efficient analytics
5. Communicate final recommendations and drive decision making
6. Telecommuting is permitted from anywhere in the U.S.
7. Master's degree in Statistics, Computer Science, or a related field. Foreign degree equivalent accepted. 24 months of experience In the job offered or in a related occupation. Experience must include 24 months in each of the following:
8. Solving analytical problems and building models using quantitative, statistical, or machine learning approaches
9. Machine learning, statistics, or other data analysis tools and techniques
10. Performing data extraction, cleaning, analysis and presentation for medium-to-large datasets
11. Programming in Python, R, Java, or C++
12. Writing SQL queries
13. Scientific computing and analysis packages such as NumPy, SciPy, Pandas, Scikit-learn, dplyr, or ggplot2
14. Statistical methods such as forecasting, time series, hypothesis testing, classification, clustering or regression analysis
15. Data visualization libraries such as Matplotlib or Pyplot
16. Machine learning libraries and packages such as PyTorch, Caffe2, TensorFlow, Keras, or Theano
**Equal Opportunity:** Facebook is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Facebook is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at firstname.lastname@example.org.