Arian Naseh

• Working alongside experienced developers taught me a lot about how to think and design products.
• Managing stakeholders, communicating, and securing their approvals was also a significant part of my job, which was new to me.
• From a technical perspective, I got to work with many new technologies and tools, mostly on the Azure cloud platform.
• I had the chance to develop ETL and inference pipelines on the Azure Machine Learning platform, create LLM-based applications, and a lot of other cool stuff.

• At Docma, I primarily focused on backend development, creating endpoints to enhance targeted advertising campaigns.
• Beyond coding, I helped the team refine their code repository for better long-term maintenance and easier onboarding of new members.
• I also dedicated significant time to debugging and designing experiments, ensuring our profiling algorithms were effective across different population segments. The goal was to maintain our data tools’ speed, reliability, and precision.

• I had never imagined that my first official job would be at the intersection of technology and indoor farming!
• At TicTie Labs, I developed a machine learning model to predict plant growth, aiding operators in meeting their demand efficiently.
• Additionally, I created dashboards to visualize live monitoring data from the farms and alert operators about conditions that were out of range.
• I also proposed and developed an Android application to help operators capture data seamlessly without disrupting their workflow.

• Fresh from completing my M.Sc. at York University, I co-founded ETF Ocean to democratize algorithmic investment strategies.
• I developed and implemented portfolio selection systems using Python, utilizing both technical and fundamental financial indicators.
• Additionally, I created modules to verify the accuracy of portfolio back-tests and designed ETL pipelines to manage large-scale historical financial data.
• I also played a key role in shaping our business model and leading our initial marketing campaigns.

During the M.Sc program, I focused my studies on machine learning and data science. I took courses on machine learning theory, data mining, advance deep neural network, data visualization, and more. My thesis is about the application of Deep Reinforcement Learning in IoT networks.

This program helped me to distance my studies from electrical engineering and pivot towards computer science. I took courses in bio-inspired artificial intelligence and statistical learning, which got me hooked on machine learning readings for the years to come.

I received my bachelor’s degree from the University of Guilan, in the beautiful city of Rasht, Iran. I did some TAship for electronics courses. For my final project, I designed an LED lamp driver and developed an android application to control the lamp’s brightness.