My List Of Data Science Roles

There is no 1 Data Scientist. How many roles can you count? Here’s my list:

1. Data & AI Strategist
2. Data Engineer
3. Data Librarian or Ontologist
4. Researcher (Hard Sciences Background)
5. Applied Researcher (Hybrid Sci-Tech Background)
6. Machine Learning Architect
7. Machine Learning Product Platform Engineer
8. Machine Learning Automation Platform Engineer
9. MLOps Engineer
10. Machine Learning Quality/Reliability Engineer
11. Data & AI Product Manager
12. AI Ethics & Compliance Analyst
13.  Data & AI Educator
14. Data & AI Evangelist/User Advocate
15. Data Scientist Leader (Manager to VP)
16. C Suite Data Scientist (CDS, CDO, CDAO, etc.)

Specific domains will add specialist roles around more complex technical use cases. Edge AI Data Scientists and Decision Scientists are two examples. They are not required today but likely will be over the next 2 years.

As research teams advance, new roles will be created to manage and improve the research process. Research Quality is an example.

Add supporting roles like Data Analysts, Cloud Architects, and Integration Engineers, this quickly becomes an organization. The D&A Organization must produce revenue to justify its existence. Cost savings alone will not sustain the investment.