2 — Gartner predicts that the ML Engineer role will 5X in the next 3 years, becoming the fastest-growing role in AI space. YET, the firm also estimates that 50% of IT leaders will struggle to move AI projects past proof of concept to production.
Some has to do with technology but a lot has to do with TEAMS. You’ve heard me talk about data teams before. Companies like Spotify, Netflix have great data teams that are getting things done. MLB, NYT…and this week I talked to PostMates, another great team you’ll hear about soon.
The question is how are you able to learn from this and replicate at your company? Should you take the example of Spotify and replicate directly?
That’s where great firms like Gartner can be useful because they talk to a lot of companies and they aggregate these learnings for you. Another great source of information is Barr Moses — CEO and co-founder of Monte-Carlo and former research assistant at Stanford.
They each have a model for the personas you need to hire into your “Data and AI Team”. While Gartner’s model identifies 4 roles (data engineer, scientist, AI architect and ML engineer), Barr identifies 6.
She has talked to over 200 data teams. She and her team have identified 6 major data personas involved in the Bad Data Blame Game. They are:
- BI Analyst
- Data Scientist
- Data Governance Lead
- Data Engineer
- Data Product Manager
What do they do?!
- Data Accessibility
- Make It Easy To Interpret the Data
- Drive Insights and Recommendations
- Maintain High Data Quality
- Deliver on Data Reliability
All of which, the CDO is Accountable for in Barr’s model. Which model do you prefer?! Compare and Contrast below!