In this first episode, Aggie Branczyk sits down with Rohan Dalton, a former experimental quantum optics researcher turned data engineer in the fintech industry. Rohan shares his personal journey that took him from the University of Queensland (Brisbane, Australia) to a hedge fund in New York City, discussing how he leveraged his problem-solving skills and self-taught programming knowledge to excel in his new role. This episode offers valuable insights into the importance of adaptability, the transferability of skills acquired during a physics PhD, and how to effectively learn new technologies on the job. Tune in to hear about Rohan’s day-to-day as a data engineer, his book recommendations, and his advice for physics students pondering their career paths.
Aggie Branczyk on LinkedIn
Rohan Dalton on LinkedIn
Podcast video on YouTube
Opening music by Alexey Ivanov from Pixabay.
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Aggie works at IBM as a Technical Program Manager for the Quantum Working Groups, and the opinions shared in this podcast are her own and are not in any way endorsed by IBM.
In this first episode, Aggie Branczyk sits down with Rohan Dalton, a former experimental quantum optics researcher turned data engineer in the fintech industry. Rohan shares his personal journey that took him from the University of Queensland (Brisbane, Australia) to a hedge fund in New York City, discussing how he leveraged his problem-solving skills and self-taught programming knowledge to excel in his new role. This episode offers valuable insights into the importance of adaptability, the transferability of skills acquired during a physics PhD, and how to effectively learn new technologies on the job. Tune in to hear about Rohan’s day-to-day as a data engineer, his book recommendations, and his advice for physics students pondering their career paths.
Aggie Branczyk on LinkedIn
Rohan Dalton on LinkedIn
Podcast video on YouTube
Opening music by Alexey Ivanov from Pixabay.
---
Aggie works at IBM as a Technical Program Manager for the Quantum Working Groups, and the opinions shared in this podcast are her own and are not in any way endorsed by IBM.