Data Scientist, Infrastructure Facebook
Boston, MA

Job Description

The Infrastructure Strategy group is responsible for the strategic analysis to support and enable the continued growth critical to Facebook's infrastructure organization. The ideal candidate will be passionate about Facebook, have strong analytical and modeling aptitude and has experience using data to drive cost effective decision making.

RESPONSIBILITIES

* Leverage data and business principles to solve large-scale web, mobile and data infrastructure problems.



Work cross-functionally to define problem statements, collect data, build analytical models and make recommendations.

Build and maintain data driven optimization models, experiments, forecasting algorithms, and machine learning models.

Leverage tools like Python, R, Hadoop & SQL to drive efficient analytics.

Communicate final recommendations and drive decision making.

MINIMUM QUALIFICATIONS

* Degree in quantitative field (e.g. Computer Science, Engineering, Mathematics, Statistics, Operations Research or other related field)



2+ years of industry or graduate research experience solving analytical problems and building models using quantitative, statistical or machine learning approaches

Experience with Machine Learning, Statistics, or other data analysis tools and techniques

Experience performing data extraction, cleaning, analysis and presentation for medium to large datasets

Experience with at least one programming language (i.e. Python, R, Java, or C++)

Experience writing SQL queries

Experience with scientific computing and analysis packages such as NumPy, SciPy, Pandas, Scikit-learn, dplyr, or ggplot2

Experience with statistics methods such as forecasting, time series, hypothesis testing, classification, clustering or regression analysis

Experience with data visualization libraries such as Matplotlib, Pyplot, ggplot2

Experience with machine learning libraries and packages such as PyTorch, Caffe2, TensorFlow, Keras or Theano

PREFERRED QUALIFICATIONS

* Advanced degree (Master's or PhD) in quantitative field



Experience working with distributed computing tools (Hadoop, Hive, Spark, etc.)

Proficiency in algorithmic complexity

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