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Job Overview

Principal Data Scientist in New York, NY, USA

  • Reference - BR-012419-1
  • Permanent
  • Competitive salary


  • Delivering statistical and machine learning models.
  • Creating and employing state-of-art technologies, building solid and complete solutions to problems and challenges.
  • Input on all aspects of the data pipeline and online evaluation.
  • Work with product managers on defining product features and key metrics/KPIs.


  • An advanced degree in data science (CS, Statistics, Mathematics, or equivalent subject), PhD preferred.
  • Track record in designing useful, consumer-oriented big data application.
  • Experience with OO and functional languages (e.g. Scala, Java, Python, OCaml, etc.).
  • Familiarity with some scientific computing packages (e.g. R, Matlab, SAS, etc.).
  • Not afraid to work complex/seemingly intractable problems.
  • Work well independently or in groups. Able to communicate effectively with others.
  • Strong foundational knowledge and experience with Machine Learning and Data Mining such as
    • Kernel machines, ensemble learning, deep learning, regularization theory
    • Active and semi-supervised learning
    • Clustering
    • Linear and nonlinear feature selection and dimension reduction
    • Statistical analysis and hypothesis tests
    • Nearest neighbor search in high dimensional space
    • Missing value imputation, etc.
  • Strong knowledge and experience with recommendation such as learning to rank, collaborative filter, etc.
  • Strong knowledge and experience with NLP such as named entity recognition, sentiment analysis, topic detection, summarization, etc.
  • Solid knowledge on operation research including linear programming, convex programming, dynamic programming
  • Solid knowledge on Graph Theory, Random Graph, Graph Mining
  • Experience with data visualizations
  • Experience with MapReduce: Hadoop, Hive, PIG, Mahout, etc.
  • GPGPU experience a plus.
  • NoSql a plus: HBase, Cassandra, Accumulo, Mongo, Neo4j, etc.
  • Experience with ETL, data warehouse and reporting