2. You listed 2 data scientists in your team - I know Machine Learning is something not everyone can grasp. Are those people qualified? What Machine Learning projects they were part of? What courses they graduated?
Yes, we are qualified enough 
I have about 3 years of experience in the area of Data Science, Machine Learning and intelligent data processing (image recognition projects). I'm PhD in Applied Mathematics and an Associate Professor of the Mathematics, Mechanics and Computer Science Institute at the Southern Federal University. I studied cs231n and Coursera Data Science course from Moscow Institute of Physics and Technology. Projects from previous job are part of NDA and cann't be shown. Current project is ukit AI.One more our team member successfully won Apple WWDC Scholarship due to her Machine Learning project. She is also finished Introduction to ML course from Moscow Institute of Physics and Technology about 2 years ago and applied for Andrew Ng course and cs231n.
AFAIK MIPT is a well known University that graduates capable professionals. Coursera is also well-known on-line education platform that hosts on-line courses. However I don't think that on-line courses really sufficient to develop something serious (it can be great introduction but hardly more). Especially in such hard topic as data science. I find suspicious that ALL your previous projects have NDA. Usually NDA have ~2 years expiration dates and since your NDA did not expired yet, I assume you are fairly new to this field. I may be wrong but you provided little to no information that can be easily proven.
Your other colleague, who won WWDC Scholarship sounds very promising. Would she be able to share her award wining project with us? She is surely listed as a winner somewhere? I assume it's not under NDA since it was submitted to public contest and won award? How did her scholarship went? She graduated?
You see I happen to have some knowledge in the topic and understand that you have to have EXCELLENT skills in Linear Algebra to even start to comprehand machine learning. Normal ML course (I mean offline course of Google or Microsoft level) lasts for a couple of years at least and only after that professional can expect to become somewhat capable. Online courses are widely available but can only serve as an indication of capability to continue learning. Usually working in companies like Google, Microsoft, Yahoo (or Yandex or Mail.ru in Russia) serves as an indication of real experience in data science.