Research Data Scientist

  • Smart Working
  • Remoto


Meta (Facebook) sta cercando una figura di Research Data Scientist in Remoto: Applica ora!
Research Data Scientist Responsibilities
  • 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 Facebook’s unparalleled data infrastructure
  • 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 capacity constraint models
  • Leverage tools like R, PHP, Python, 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)
  • 1+ 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 or Equivalent experience) in quantitative field
  • Experience working with distributed computing tools (Hadoop, Hive, Spark, etc.)
  • Proficiency in algorithmic complexity (,