This is an AAO appeal decision — a case denied once and appealed. It shows how the framework is applied; it is not the filing population.
The Petitioner, a data scientist working in the information technology sector, proposed to provide expert data analytics services in the U.S. to advance the use of data science across industries.
Field: data science · Read the decision (uscis.gov)
EB-2 threshold — addressed
Director found Petitioner qualified for EB-2 classification as an advanced degree professional based on his master's degree in data science; not disputed on appeal.
Prong 1 — national importanceestablished
Prong 2 — well positionedestablished
Prong 3 — balance of factorsestablished
How the evidence was treated
- recommendation letter · credited
- citations publications · credited
- resume experience · credited
- degree · credited
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Notable
AAO sustained the appeal, finding all three Dhanasar prongs satisfied and reversing the Director on national importance, well-positioned, and balance-of-benefit prongs; applied the STEM-field 'strong positive factor' policy guidance favorably.
Authorities this decision leans on
From the doctrinal survivor set — 187 authority tests across 47 distinct authorities cleared the differential-lift gates. Only those appear here.
- 8 C.F.R. 103.3
- 8 C.F.R. 204.5(k)(2)
- Flores v. Garland
- USCIS Policy Manual F.5(D)(2)
What this case teaches
Analyst reading of the decision text.
AAO found petitioner's STEM advanced degree, published research, employer/mentor endorsements, and generic data-science industry importance sufficient to satisfy all three Dhanasar prongs on de novo review.
Pair strong personal credentials and STEM classification with even generic industry-importance evidence; AAO may find this sufficient without granular scale analysis.
moderate
critical_emerging_tech · stem_positive_factor · us_competitiveness · economic_growth_generic
mixed
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