The value of an organization’s data is heavily impacted by how that data gets put to use. And the people responsible for doing that—analysts and data scientists—seem to be perpetually in short supply. As of this rebroadcast, there is ample demand for moderately priced unicorns who have at least five years of experience in SQL, Google Analytics, Python, Adobe Launch, statistical modelling, R, dashboard design, Excel, Power BI, Google Tag Manager, and Adobe Analytics… with excellent time management and communication skills. Perhaps, if you’re a hiring manager, this episode might be one you suggest that your recruiters listen to? Just tell them it includes the exact job description for that open req you’ve got!
For complete show notes including transcript and links to items mentioned in the show, see the original show page: #117: What’s in a Job Title? Maybe the Data Shows with Maryam Jahanshahi
What’s in a job title? that which we call a senior data scientist by any other job title would model as predictively…
This, dear listener, is why the hosts of this podcast crunch data rather than dabble in iambic pentameter. With sincere apologies to William Shakespeare, we sat down with Maryam Jahanshahi to discuss job titles, job descriptions, and the research, experiments, and analysis that she has conducted as a research scientist at Datapeople (formerly TapRecruit), specifically relating to data science and analytics roles. The discussion was intriguing and enlightening!
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