Success Stories: NIW Petition Approved for Algorithmic Trading and Quantitative Researcher in New Jersey in the Field of Financial Econometrics
Client’s Testimonial:
This is fantastic news! [...] I am very pleased and honored to make recommendations of WeGreened on mitbbs.com and huaren.us ( first I need to register!), or anywhere!
On April 16th, 2015 We Received EB-2 NIW (National Interest Waiver) Approval (Approval Notice) for an Algorithmic Trading and Quantitative Researcher in the Field of Financial Econometrics
Position at the Time of Case Filing: Algorithmic Trading and Quantitative Researcher
Country of Origin: China
Service Center: Texas Service Center (TSC)
State of Residence at the Time of Filing: New Jersey
Approval Notice Date: April 16th, 2015
Processing Time: 6 Months, 17 Days
The client that North America Immigration Law Group – WeGreened.com had the opportunity to work with in this case was an Algorithmic Trading and Quantitative Researcher from China. He conducts his research on a highly specialized area focusing on the development of statistical models and algorithms in quantitative financial services. We successfully demonstrated that his continued employment in the field would benefit those in his field, as well as the citizens of the United States at large. In order for our client’s case to be successful, we submitted extensive documentation proving his highly significant contributions to his field, including 5 peer-reviewed scientific articles published in leading journals and more than 10 conference papers and presentations at national and international conferences and seminars. His publications had been cited at least 110 times at the time we filed the case; nearly all of the citations were by independent researchers around the world, demonstrating that these publications are widely recognized and relied upon in the field. The importance of his work was confirmed in the following quote from an independent recommender, “It may also be important to note that [client] has completed research related to Bayesian Statistical Learning. This work resulted in a Bayesian learning algorithm that solves the problem of packet drop rate optimization… It is also essential to emphasize that [client’s] work in this area can be applied to other data mining and machine learning problems, and has thus offered value to not only researchers working in the area of wireless networks, but to his [client’s] current research related to algorithmic trading.” Through extensive documentation, we were able to successfully argue that our client would serve the national interest to a significantly greater degree than others with similar education and experience. His NIW petition was approved in 6 months and 17 days.