The American Statistical Association is launching a voluntary data science certification program with two credentials: Data Science Professional (DSP) and Advanced Data Science Professional (AdvDSP). Distinguish yourself by earning these designations. ASA members who earn them signal to employers, colleagues, and the field that their data science expertise has been recognized and validated.
Developed with the Alliance for Data Science Professionals, including the Royal Statistical Society and Alan Turing Institute, this program defines rigorous standards for data science practitioners.
Why Certification, and Why Now?
Data science has matured rapidly from an emerging field into a foundational professional discipline. Organizations of all kinds rely on data scientists to build models that shape policy, analyze data that inform medical decisions, and deploy algorithms that affect millions of people’s lives. Just as PStat has long recognized professional statisticians, the ASA now offers a broadly recognized credential to signal professional competence in data science.
The ASA has long been a leading voice on standards and good practice for statistics, well before we launched statistics accreditation in 2010. Certification of data scientists is a natural step, providing a concrete, practitioner-level mechanism for the community to recognize members who have voluntarily demonstrated they meet high professional standards.
Designation of DSP or AdvDSP signals its holder has proactively sought peer review of their credentials, submitted a portfolio that has been carefully evaluated by distinguished peers, and committed to ongoing professional development and ethical practice.
About the DSP and AdvDSP Credentials
The certification program offers two tiers that reflect different levels of professional responsibility, decision-making authority, and organizational impact.
The DSP credential is designed for practitioners with at least two years of documented data science experience who take personal responsibility for their work, including its ethical dimensions. DSP applicants must demonstrate applied knowledge and understanding in at least three of the five skill areas defined by the Alliance for Data Science Professionals—(A) data privacy and stewardship; (B) data engineering, architecture, storage, and curation; (C) problem definition and communication; (D) problem solving, analysis, modeling, and visualization; and (E) evaluation and reflection. They must also show competence in applying technical skills to deliver meaningful outcomes.
The DSP credential is designed for practitioners with at least two years of documented data science experience who take personal responsibility for their work.”
The AdvDSP credential recognizes senior practitioners with at least five years of documented experience who are fully accountable for their own work and that of others. AdvDSP applicants must demonstrate deep expertise in Skill Area E (which covers reflective practice and ongoing professional development) and at least two additional skill areas, while maintaining general competence across the remaining areas. AdvDSP holders typically advise at the strategic level, hold significant decision-making authority, and consider the broad organizational and societal impact of their work.
Both credentials are portfolio-based rather than examination-based. Applicants submit an application that includes personal information, academic and training history, competencies and responsibilities, work experience, and continuing professional development. The Data Science Certification Committee might also request additional materials, a personal statement, or an interview before reaching a decision.
Ethics at the Core
Ethics is woven into the ASA data science certification process. All applicants must agree to uphold the ASA’s Ethical Guidelines for Statistical Practice. Demonstrating ethical awareness is integral to satisfying the skill area requirements. From responsible data collection and model validation to transparent communication of results and awareness of relevant privacy and legal frameworks, the program expects certified members to reflect on the ethical dimensions of their practice and incorporate those reflections into their work.
ASA Membership Required
To apply for DSP or AdvDSP certification, applicants must be current ASA members and maintain that membership to retain their certified status. If ASA membership lapses, so does certification. ASA membership connects certified practitioners to an engaged professional community with ongoing access to ASA resources, publications, and networks.
How to Apply
Applications may be submitted at any time through the ASA’s online data science certification portal. To complete an application, you will need to submit the official application form, along with supporting materials covering your academic and training background, professional experience, competency demonstrations across the relevant skill areas, and a record of continuing professional development.
A nonrefundable application fee is required before a submitted application will be reviewed. Applicants who are not approved will receive written feedback from the DSCC and may reapply. Successful applicants will be assessed an annual maintenance fee to maintain their certified status, with certification renewal required every five years.
A New Chapter for the Data Science Profession
The launch of the ASA’s data science certification program reflects our deep commitment to the data science community and the public it serves. By partnering with the Alliance for Data Science Professionals and Royal Statistical Society, we have ensured that ASA certification meets broad standards while remaining grounded in the ASA’s tradition of statistical rigor, ethical practice, and service to science and society.
We invite ASA members actively engaged in data science to explore the program and consider whether the DSP or AdvDSP credential is right for them. Voluntary certification is a concrete opportunity to have your expertise recognized by peers, differentiate yourself to employers, and deepen your commitment to ethical and rigorous practice—whether you are mid-career or a seasoned leader in the field.
Get the details about eligibility, application requirements, fees, and program guidelines.
Meet the Data Science Certification Committee
All certification decisions are made by the ASA’s Data Science Certification Committee, a body of AdvDSP-certified members who are broadly representative of the membership. Committee members serve staggered three-year terms and are appointed by the president-elect. The DSCC is also charged with providing constructive feedback to applicants who are not approved and making recommendations to the ASA Board of Directors regarding improvements to the certification process. The inaugural DSCC consists of the following members:
- Randy Bartlett
- Melanie Edwards
- Jen Gibson
- Rick Ittenbach
- Colleen Kelly
- Melissa Kovacs
- Albert Lee
- Eric Tesdahl
- Teri Utlaut (chair)
Applications for certification are reviewed in confidence by the DSCC. Members of the DSCC who have a conflict of interest with respect to an applicant are required to recuse themselves from that review, and applicants may identify up to three committee members they believe may have such a conflict.
(A) data privacy and stewardship; (B) data engineering, architecture, storage, and curation; (C) problem definition and communication; problem solving, analysis, modeling, and visualization; and (E) evaluation and reflection
Typo…no part D
Thank you Jeff. We have corrected this typo.
Is this certification intended or appropriate for educators at teaching institutions who consult occasionally, but focus on teaching statistics and data science students the ideas embedded here, and evaluate their ability to meet them?
Hi Sam, While the intended target audience for data science certification is practicing data scientists, it may be entirely appropriate in certain circumstances for faculty who both practice data science and train students to be statisticians and data scientists to be certified. We encourage you to apply so our Data Science Certification Committee has the opportunity to review and respond.