Data science

From fitting models to deciding whether a model was the right answer at all.

← All paths

The steps

Entry

Experienced

Senior

Lead / Principal

Junior data scientist
Data Scientist
Senior Data Scientist
Principal Data ScientistSpecialist

PromotionLateral move or track changeEach step links to its full detail below.

#	Step	What changes here	Jump	Skills
1	Junior data scientistEntry · Individual contributorNo active openings	Moves from the analysis notebook to a result somebody uses.	—	SQL Python Statistics
2	Data ScientistExperienced · Individual contributorNo active openings	Chooses the method instead of being handed one.	PromotionJump: Moderate	Statistics Feature engineering Machine learning Experimentation and A/B testing
3	Senior Data ScientistSenior · Individual contributorNo active openings	Answers for the model’s impact, not its accuracy.	PromotionJump: Moderate	Metrics definition Data storytelling Experimentation and A/B testing ML operations
4	Principal Data ScientistLead / Principal · SpecialistNo active openings	Sets the company’s research agenda.	PromotionJump: Moderate	AI literacy Machine learning Technical communication Strategic planning Cross-functional leadership

What makes the differenceAlso asked for

This describes moves that happen, not a recommended sequence or the only way to get there.

How this path was built

A structured starting point: it describes how this function is organized in technology companies, not a survey of Costa Rican employers. The skills at each step come from the platform’s curated vocabulary. Each version goes through industry review before it replaces this one.

Evidence as of: August 16, 2026
Reviewed on: August 16, 2027