We respect the privacy of our clients and the hard work they do to maintain their competitive advantages. Your privacy is our priority.
We have unquenchable thirst for the latest trends and technologies in information theory. We love to stay prepared for the new challenges the universe may bring us.
We enjoy providing precise, self-sufficient, and simple solutions. We believe that coherent communication is the key to fruitful relationships.
We are excited by new challenges we can apply our skills to. We love fixing all kinds of complicated and seemingly unsolvable problems.
The Byteflow Dynamics team is a close-knit group of professionals who strive to deliver high-quality solutions. Many of us embarked on collaborations in the early years of graduate school and are happy to continue the professional development together. It is this bond which has created an environment for fruitful exchange of ideas and a great learning atmosphere.
Andi has served as the Chief Executive Officer of Byteflow Dynamics since its inception,
putting business forward by working closely with clients in addressing their business needs, providing
with scientific solutions. He is personally involved in all the projects and has brought together
a close-knit group of data scientists
and engineers to help clients with data science solutions,
data science training and improve their data workflow using agile solutions.
Education: Mathematics from Hunter College (BS). Quantum Information Theory from The Graduate Center CUNY (PhD).
Kay is passionate about leading data science teams in finding innovative solutions to challenging
She became an expert in statistical modeling while solving the mysteries of the universe
in her exploration for brown dwarf atmospheres. To communicate her findings, she felt that design was
an important element of any project.
Education: Astronomy from University of Arizona (BS), City University of New York (PhD).
With a background in quantum optics and teaching, Gina has developed
a wide range of experiences in software engineering, data analytics and explaining her findings
to a wide audience. She is
equally passionate about model building and finding insights in data as well as teaching the
next generation of data scientists and physicists.
Education: Physical Engineering form Teconológico de Monterrey, Mexico (BS), Physics from Unicersidad de Concepción, Chile (PhD).
Sergey enjoys spending time in figuring out the appropriate and optimal algorithms for specific cases.
He makes sure we are always using the most up-to-date tools and libraries
in our works.
Education: Physics from Belarusian State university(MS), Computational Physics from The Graduate Center, CUNY (PhD).
Armando holds an MD and a MSc. in Biomedical Sciences from his alma mater in Madrid.
He has been clinically active for several years in different hospitals across New York City.
Armando’s clinical expertise span over the fields of Internal Medicine at
Albert Einstein College of Medicine, clinical trials development,
and neurocognitive research at Icahn School of Medicine at Mount Sinai.
Among his goals are utilizing statistical modeling to better understand
disease finding new ways to benefit from
passively monitoring patients to constrain costs and maximize outcomes.
Education: Medical Doctor from University Complutense of Madrid (M.D.), Biomedical Sciences from University Complutense of Madrid (M.S.).
Drawing on his experience as an Economics lecturer, program analyst, and large household data management,
Daniel brings in a unique experience to both analytics and data infrastructure.
Education: Advanced Economic and Policy Analysis from Columbia University (MS).