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Samuel Trost

Data Scientist, New York, USA
/ / What I do at Synechron

Data Scientist working on data modelling and statistical analysis

As a member of Synechron’s Global Data Science Center of Excellence and sitting in our New York global headquarters, I wear many hats. I am primarily a data scientist which means working on data modelling and statistical analysis, but I also contribute to data engineering, system administration, and big data architecture initiatives for Synechron’s global tier one banking clients. I also played an active role in the development of Synechron’s AI Data Science Accelerators


Sam, as a Data Scientist, wears many hats helping on initiatives including data engineering, system administration, and big data architecture

/ / Why I joined Synechron

Exposure to all of the innovation currently happening in FinTech

I have a (relatively) strong math background. I worked with data in my previous job in the semiconductor industry and have always loved programming, so data science was a natural next step. I joined Synechron because I thought the company would give me exposure to all of the innovation currently happening in FinTech.

/ / MY SKILLs, qualifications and experience

Chemical engineering, Data Science and the Internet of Things (IoT)

I hold a bachelor’s degree in Chemical engineering and have done a data science boot camp which set me on the path I am on today. My first job was as a process engineer where I focused on troubleshooting chemical processes by analyzing data from sensors in chemical process management tools used in semiconductor production combining data analysis and Internet of Things (IoT). Initially, I taught myself Python and reinforced this knowledge through the boot camp and now via active research and development and client work learned at Synechron.

/ / My personal interests

e-sports (competitive gaming) and Data Science

In my spare time, my hobbies include video games – mainly esports (competitive gaming). The game itself that I love the most is called Dota 2. I’m also interested in the tons of data science work being done on the competitive side to help give teams an edge over their competition. For example, OpenAI has developed an AI in Dota 2 that can control a team of five to play together against human players via reinforcement learning. Reinforcement learning is also something that is seeing a lot of growth in finance.

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