World Economic Forum identified the top 3 growing jobs are:
1) Data Analysts and Data Scientists
2) AI and Machine Learning Specialists
3) Big Data Specialists
These โDataโ based roles can be broadened into 3 main buckets: Analysts, Scientists, and Engineers. The skills of these roles can easily overlap, but what makes them distinctly different is their focus.
๐๐๐ญ๐ ๐๐ง๐๐ฅ๐ฒ๐ฌ๐ญ:ย A person who specializes in making sense out of past and current numerical data to find answers to business questions and help business leaders make better decisions.ย (๐ด๐๐ ๐ ๐๐๐๐ค๐ ๐๐ ๐ต๐ข๐ ๐๐๐๐ ๐ ๐ด๐๐๐๐ฆ๐ ๐ก ๐คโ๐๐ ๐๐๐๐๐๐๐ ๐ก๐ ๐๐ข๐ ๐๐๐๐ ๐ )
โช๏ธย ๐ ๐จ๐๐ฎ๐ฌ:ย Storytelling, trend analysis, presenting business simulations, understanding business requirements, creating visualizations
๐๐๐ญ๐ ๐๐๐ข๐๐ง๐ญ๐ข๐ฌ๐ญ:ย A person who specializes in building analytic and predictive models (with data received from data engineers) to interpret complex data.
โช๏ธย ๐ ๐จ๐๐ฎ๐ฌ:ย Applying statistical/machine learning tools to classify patterns, determining strength of patterns and relationships, quantifying cause-and-effect, training and optimizing machine learning models
๐๐๐ญ๐ ๐๐ง๐ ๐ข๐ง๐๐๐ซ:ย A person who specializes in building, testing, optimizing, and maintaining the data ecosystems that allow data scientists and analysts to perform their work.
โช๏ธย ๐ ๐จ๐๐ฎ๐ฌ:ย Designing the big data infrastructure and preparing it to be analyzed, building complex queries to create โpipelinesโ, cleaning data sets, and arranging problems (typically given by data scientists) in the programmed system
Knowing these definitions are not universally agreed upon - what thoughts do you have?
Graphic Idea:ย https://lnkd.in/egdsjVFA
Credits: My colleague/supporter/male ally Jeff Winter!
Editing this post and emphasizing that now-a-days domain knowledge is necessary for every single role.
#datascientists #dataanalytics #datascience #bigdata #ai #data
1) Data Analysts and Data Scientists
2) AI and Machine Learning Specialists
3) Big Data Specialists
These โDataโ based roles can be broadened into 3 main buckets: Analysts, Scientists, and Engineers. The skills of these roles can easily overlap, but what makes them distinctly different is their focus.
๐๐๐ญ๐ ๐๐ง๐๐ฅ๐ฒ๐ฌ๐ญ:ย A person who specializes in making sense out of past and current numerical data to find answers to business questions and help business leaders make better decisions.ย (๐ด๐๐ ๐ ๐๐๐๐ค๐ ๐๐ ๐ต๐ข๐ ๐๐๐๐ ๐ ๐ด๐๐๐๐ฆ๐ ๐ก ๐คโ๐๐ ๐๐๐๐๐๐๐ ๐ก๐ ๐๐ข๐ ๐๐๐๐ ๐ )
โช๏ธย ๐ ๐จ๐๐ฎ๐ฌ:ย Storytelling, trend analysis, presenting business simulations, understanding business requirements, creating visualizations
๐๐๐ญ๐ ๐๐๐ข๐๐ง๐ญ๐ข๐ฌ๐ญ:ย A person who specializes in building analytic and predictive models (with data received from data engineers) to interpret complex data.
โช๏ธย ๐ ๐จ๐๐ฎ๐ฌ:ย Applying statistical/machine learning tools to classify patterns, determining strength of patterns and relationships, quantifying cause-and-effect, training and optimizing machine learning models
๐๐๐ญ๐ ๐๐ง๐ ๐ข๐ง๐๐๐ซ:ย A person who specializes in building, testing, optimizing, and maintaining the data ecosystems that allow data scientists and analysts to perform their work.
โช๏ธย ๐ ๐จ๐๐ฎ๐ฌ:ย Designing the big data infrastructure and preparing it to be analyzed, building complex queries to create โpipelinesโ, cleaning data sets, and arranging problems (typically given by data scientists) in the programmed system
Knowing these definitions are not universally agreed upon - what thoughts do you have?
Graphic Idea:ย https://lnkd.in/egdsjVFA
Credits: My colleague/supporter/male ally Jeff Winter!
Editing this post and emphasizing that now-a-days domain knowledge is necessary for every single role.
#datascientists #dataanalytics #datascience #bigdata #ai #data
