Data Scientist

  • Must have a range of mathematical and analytical skills, as well as business acumen.
    Big data scientists analyze and integrate multiple data sets and make
    recommendations based on their findings.
  • Selecting features, building and optimizing classifiers using machine learning techniques
  • Data mining using state-of-the-art methods
  • Extending company’s data with third party sources of information when needed
  • Enhancing data collection procedures to include information that is relevant for building analytic systems
  • Processing, cleansing, and verifying the integrity of raw data used for analysis
  • Doing ad-hoc analysis and presenting results to leaders in order to support business decisions
  • Developing and applying metrics and prototypes that can be used to drive business decisions
  • Identifying emerging trends and opportunities for business growth
  • Creating automated anomaly detection systems and constant tracking of its performance


  • Experience in programming languages, such as Python or Java, is required.
  • Excellent understanding of machine learning techniques and algorithms, such as k-NN,
    Naive Bayes, SVM, Decision Forests, etc.
  • Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, etc.
  • Great communication skills
  • Experience with data visualization tools, such as D3.js, GGplot, etc.
  • Proficiency in using query languages such as SQL, Hive, Pig, etc.
  • Experience with NoSQL databases, such as MongoDB, Cassandra, HBase, etc.
  • Good applied statistics skills, such as distributions, statistical testing,
    regression, etc.
  • Good scripting and programming skills
  • Data-oriented personality