Salfo Bikienga

PhD in Statistics and in Economics with advanced knowledge of Natural Language Processing. Strong background in economics, econometrics, and statistics. 7+ years of experience working with data, teaching statistics at undergraduate and graduate levels; and working as a Data Scientist for a consulting firm. Deep theoretical and practical knowledge of descriptive and predictive modeling.

RESEARCH AND PROFESSIONAL EXPERIENCE

  1. Developed web applications and visualization tools that tell a “story” focused on insights conducive to forecasting models improvement.
  2. Applied topic modeling to demonstrate that political leaders’ consistency over economic issues predict positive economic outcome.
  3. Applied Variational Bayes methods to create a Supervised Topic Modeling Algorithm that improves topics predictive power.

PROJECTS

    1. Maintain a blog: ​http://www.salfobikienga.rbind.io/
    2. Built Shiny Web Applications for exploratory data analysis:
      1. https://bbr-cba-unl-human-capital.shinyapps.io/MyShiny/​;
      2. ​https://salif.shinyapps.io/topic_context/
    3. Built a big data missing missing values and outliers detection tool, combined with a missing data imputation method, for time series data.

TECHNICAL SKILLS

Machine Learning: ​Classification, Clustering, Natural Language Processing…

Statistical Methods:​ Design of Experiments, Latent variables models such as: Principal Component Analysis, Factor Analysis, Canonical Correlation Analysis, Structural Equation Modeling, Partial Least Squares Modeling.

Econometrics: ​Time Series Analysis, Panel or Longitudinal Data Analysis, Quasi-Experiment Methods, Regression Methods such as: OLS, Logistic Regression, Quantile Regression…

Software and Programming Languages: ​R programming, Python, SAS, SQL EDUCATION

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