RSS Featured Blog Posts
  • Intro to Data Science for Managers [Mindmap]
    Data science has become an integral part of many modern projects and businesses, with an increasing number of decisions now based on data analysis. The data science industry is experiencing an acute …
    Igor Bobriakov
  • 29 Statistical Concepts Explained in Simple English - Part 3
    This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, cross-validation, model fitting, and many more. To keep receiving these articles, sign up on…
    Vincent Granville
  • The Key to Unlock Digital Transformation
    Digital Transformation is exploiting digital technologies and data to enhance the firm’s business model. Unfortunately, a Forbes study says that 84% of the Digital Transformation initiatives fail. There are many reasons for this and one important reason is tied to the way businesses inherently operate. Basically, businesses exist to earn profits and driving profits or […]
    Prashanth Southekal, PhD
  • 10 signs you might be ready to let your inner data scientist out.
    1) You can picture yourself being introduced as a data scientist without blushing. Data science is more than a career, it is a lifestyle that requires committing to be a lifelong learner with all the trade-offs that entails. If the idea of "data science" seems over hyped and hokey then you most likely will not […]
    Phil Hummel
  • Weekly Digest, November 12
    Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. Announcements Jump-start your career as a data scientist, data engineer, or analytics manager in…
    Vincent Granville

The Data Science Interview – Classroom Assessment

  1. Send your data science candidate to a full day assessment workshop. They will be given a complex problem to solve that assesses their capabilities across disciplines. $1750 per interview
  2. Based on our classroom observations we will provide a rating of Data Science Leader, Data Science Expert, Data Engineer, Data Analyst or Not Recommend.
  3. Ratings
    • Data Science Leader – technically skilled, creative problem solver, effective communicator, applies the appropriate data science models to solve various business problems and personality to work well with team and management
    • Data Science Expert – technically skilled, creative problem solver, applies the appropriate models to solve various business problems
    • Data Engineer – technically skilled, works well with data integration aspects within the assessment, requires more cross disciplined experience to fill a data scientist role
    • Data Analyst – technically adept, creative with data visualization, effective communicator at translating data outcomes, lacks computer science skills, requires skill development and cross discipline experience to fill a data scientist role