- #1
EngWiPy
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Hello,
After finishing my PhD in EE/wireless communication from Canada, I could secure postdoc positions in the academia. But wanted to make a transition to the industry because it pays more and it is more stable. Applied to telephone companies for R&D positions, with no luck. I tried more technical positions, again with no luck. After explaining my issue here, some members suggested to search for data science positions because of my analytical background. I started reading about the topic, and I have been interested in it. So, I have applied for many positions, but with no luck so far as well.
At this stage I am not sure if investing more time learning about data science will enhance my chances given that I have no experience, and the responses are not encouraging. I have been unemployed for more than a year trying to secure job in the field of data science, during which I have been taking courses and reading materials in the topic. I am interested in the field of data science, but I am afraid by continuing doing this, I will get nothing from neither data science nor my specialization.
My question is: which is better, to keep learning for data science positions, or to capitalize on my specialization? The opportunities for my specialization are less compared to data science, but in the field of data science I am less competitive given my lack of experience, in a highly competitive and hot field!
Thanks in advance
After finishing my PhD in EE/wireless communication from Canada, I could secure postdoc positions in the academia. But wanted to make a transition to the industry because it pays more and it is more stable. Applied to telephone companies for R&D positions, with no luck. I tried more technical positions, again with no luck. After explaining my issue here, some members suggested to search for data science positions because of my analytical background. I started reading about the topic, and I have been interested in it. So, I have applied for many positions, but with no luck so far as well.
At this stage I am not sure if investing more time learning about data science will enhance my chances given that I have no experience, and the responses are not encouraging. I have been unemployed for more than a year trying to secure job in the field of data science, during which I have been taking courses and reading materials in the topic. I am interested in the field of data science, but I am afraid by continuing doing this, I will get nothing from neither data science nor my specialization.
My question is: which is better, to keep learning for data science positions, or to capitalize on my specialization? The opportunities for my specialization are less compared to data science, but in the field of data science I am less competitive given my lack of experience, in a highly competitive and hot field!
Thanks in advance
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