Category Archives: Data Science Careers

Advancing Your AI Career

Posted on January 13, 2020 by

“AI Career Pathways” is designed to guide aspiring AI engineers in finding jobs and building a career. The table above shows Workera’s key findings about AI roles and the tasks they perform. You’ll find more insights like this in the … Continue reading →

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KDD 2020 Opens Call for Research and Applied Data Science Paper Submissions

Posted on December 9, 2019 by

ACM SIGKDD Invites Industry and Academic Experts to Submit Advancements in Data Mining, Knowledge Discovery and Machine Learning for 26th Annual Conference in San Diego Read more here

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Logistic Regression in R: A Classification Technique to Predict Credit Card Default

Posted on November 11, 2019 by

Logistic regression is one of the statistical techniques in machine learning used to form prediction models. It is one of the most popular classification algorithms mostly used for binary classification problems (problems with two class values; however, some variants may … Continue reading →

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The $250K Median Salary of Data Scientists Managers is Why Google and Salesforce Invested $20B in Self-Service Data Science

Posted on June 25, 2019 by

Earlier this month, Salesforce announced the acquisition of data visualization and analytics leader Tableau for $15.7 billion and Google announced the acquisition of data discovery and analytics platform Looker for $2.6 billion. Both acquired companies will beef up the acquiring … Continue reading →

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Hyper Job Growth for Data Science and Analytics

Posted on May 22, 2017 by
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Data Science Skills: Domain Expertise, Programming, Statistics

Posted on January 30, 2017 by

Source: Business Over Broadway Based on a study of 620+ data professionals, we found that data science skills fall into three broad areas: domain expertise (in our case, business), technology/programming and math/statistics.

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9 Categories of Data Scientists

Posted on November 3, 2016 by

DataViz: Those strong in statistics: they sometimes develop new statistical theories for big data, that even traditional statisticians are not aware of. They are expert in statistical modeling, experimental design, sampling, clustering, data reduction, confidence intervals, testing, modeling, predictive modeling … Continue reading →

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