Jan 17, 2019 - 02:47 PM
• Experience with multiple actual big data projects.
• Deep knowledge of advanced analytical and statistical techniques.
• Hard-core graduate-level quantitative training.
• High proficiency in the right programming languages and tools.
• Business acumen, along with a working knowledge of the subject matter.
• Great curiosity, tempered by healthy amounts of both confidence and humility.
Recruiters want to conclude from a data science resume that the candidate can get to work very fast, often on ill-defined problems, figuring out workable solutions within a business context very quickly, and doing so without a lot of hand-holding,
Data science applicants need to understand that employers are not there to subsidize a self-styled intelligentsia. There is no shortage of folks who can load up their resumes with bullet points covering arcane statistics, nonesuch analytical techniques, and virtuoso coding claims. Recruiters want candidates who can apply it all to transforming servers full of data into cash flows, capitalizable assets, and competitive advantage.
Recruiters absolutely do not want to see resumes that portray helpless wonks who constantly need someone to tell them what to do next. They also do not want to see resumes that portray an applicant as someone who is hell-bent on proving they are the smartest person in the room, all the time.
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Aug 15, 2018 - 03:03 AM