Lead Data Scientist

Job description



  • Deep expertise in machine learning techniques (supervised and unsupervised) statistics / mathematics / operations research including (but not limited to):
  • Advanced Machine learning techniques: Decision Trees, Support Vector Machines, Clustering, Bayesian Networks, Reinforcement Learning, Feature Reduction / engineering, Anomaly deduction, Natural Language Processing (incl. Theme deduction, sentiment analysis, Topic Modeling).
  • Statistics / Mathematics: Data Quality Analysis, Data identification, Hypothesis testing, Univariate / Multivariate Analysis, Cluster Analysis, Classification/PCA, Factor Analysis, Linear Modeling, Logit/Probit Model, Affinity & Association, Time Series, DoE, distribution / probability theory.
  • Operations Research: Sensitivity Analysis, Multi-criteria decision-making.
  • Strong experience in specialized analytics tools and technologies including but not limited to : Python, R, Data Bricks, Apache Spark, Hadoop.