Study Goals: Benchmark Traits of Analytics Professionals
- The growth of the analytics discipline has created a drastic increase in requirements for analytics professionals.
- This explosion has created confusion about where to find analytics professionals and what backgrounds, skills and traits define top performers in this field. See below for details.
Talent Analytics, Corp. and the International Institute for Analytics are conducting an Industry-wide, global Study to end the confusion and debating. Results are sure to provide value to those needing to find, hire, manage and retain analytics professionals in their organizations.
Call to Arms: Benchmark your team of Analytics Professionals
Call to Arms: Analytics Professionals Study Q&A
Click here to watch the 20 minute Q&A with Talent Analytics CEO Greta Roberts.
Shortfall Forecasted for Analytics Professional
McKinsey Global Institute
- By 2018, the US could face a shortage of 140,000 to 190,000 analytics professionals.
- An emerging talent gap exists between organizational needs and current industry capabilities.
- 64% of data scientists believe technology will outpace the supply of available talent.
- Our capacity to train new data scientists is not keeping up.
- 2/3 of respondents foresee a shortfall of data scientists over the next 5 years.
Smart Data Collective: Don Willmott
- Big data will need 1.5 million data scientists.
- Not enough people who know how to take advantage of Big Data.
CIO.com: Bob Violino
- Every single client I talk to tells me they are struggling with finding and retaining BI talent.
- There’s a BI talent shortage.
Venture Beat: George Mathew, President & COO Alteryx
- There aren’t enough data scientists for the next decade.
Institute for Advanced Analytics, NC State University
- Individuals with analytics skills are in short supply.
- Employer demand for analytics talent is projected to intensify.
Confusion: What Makes a Top Analytics Professional
Data Informed, Michael Goldberg
- Data Cruncher
IBM, Anjul Bhambhri
- Part analyst, part artist.
- Strong business acumen
- Ability to communicate with business and IT
- Can stare at data and spot trends
WSJ – Bit.ly Chief scientist: Hilary Mason
- Model data sets mathematically
- Understand the math required to build models
- Engineering skills
- Someone who can find insights and tell stories from data
- Ask the right questions
Institute of Analytics Professionals of Australia, Peter O’Hanlon
- Smartest algorithm builder
- Data engineer
- Spreadsheet jockey
- Business analyst
- Don’t assume they will have a stats or computer science background
Accenture Analytics, Stacy Blanchard
- Statisticians who are deep into data modeling
- They’re close to the technology
- They know the right algorithms to use with the data available
mathbabe, Cathy O’Neil
- Speaks clearly, directly
- Emphasizes skepticism
- Ready to vent about how people trust models
- Pushy enough to speak up at a meeting
- That annoying person who holds people back from drinking too much kool-aid
- Naturally curious
- Remarkably educated
- 40% have a master’s degree
- Additional 17% have a doctorate
- Over 90% have at least a college education
O’Reilly Strata, DJ Patil
- Technical expertise
Ngoni Chikombia is a Marketing Associate at Talent Analytics, Corp. He can be reached via email@example.com.