Data Science Council of America (DASCA) structures its certifications across clearly defined levels and domains to reflect increasing responsibility, complexity, and professional maturity in data-driven roles.
DASCA certifications are organized into progressive levels that align with career stage rather than academic background alone.
Progression across levels is not automatic. Each certification has defined expectations, and candidates are expected to demonstrate readiness appropriate to the certification they attempt.
In addition to levels, DASCA certifications are organized across distinct but related domains:
Each domain reflects different professional roles and responsibilities. While there may be conceptual overlap, certifications are designed to assess domain-specific competence.
To help determine the certification that best aligns with your academic background and professional experience, use the Eligibility Checking Tool.
Not all domains necessarily follow identical level structures, and not every professional is expected to progress through every level or domain. DASCA’s framework allows candidates to pursue certifications that align with their role, experience, and career direction rather than a single linear pathway.
Certification structure is reviewed periodically to ensure continued relevance to evolving industry practices, technological shifts, and professional expectations.
DASCA certifications are structured to provide clear differentiation by both career stage and functional domain, enabling employers, institutions, and professionals to interpret credentials with clarity and confidence.