Should I Switch Careers? Career Advice for Data Science

In summary: It's possible to get a visa, but it's not something you can just decide to do and then do it; you need to have a company that is willing to sponsor you for one, and getting a company to sponsor you for a visa in the US is rather difficult. In summary, the individual is facing a tough decision between continuing to pursue data science positions or capitalizing on their specialization in wireless communications. They have been unsuccessful in finding a job in either field so far and are limited by their citizenship and geographic location. They are considering the possibility of applying for jobs in other countries, but the visa process can be difficult. They are also contemplating doing a postdoc in the US to improve their chances of landing a job with a
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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
 
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  • #2
S_David said:
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!
You seem to be going in circles. You started exploring opportunities in data science because you couldn't find a job based on your expertise in wireless communications. So what has changed now that would improve your chance of finding a job based on your expertise in wireless communications (which falls further out of date as time passes and you are not actively engaged in the field)? You may have to consider strongly whether your constraints of citizenship and geographic location is too limiting.
 
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  • #3
CrysPhys said:
You seem to be going in circles. You started exploring opportunities in data science because you couldn't find a job based on your expertise in wireless communications. So what has changed now that would improve your chance of finding a job based on your expertise in wireless communications? You may have to consider strongly whether your constraints of citizenship and geographic location is too limiting.

Right, but after a year of trying in the field of data science, my chances don't look good as well, so I am back to the thought whether it is a good idea to change careers or not. My citizenship and geographic location probably have a role. I have restricted myself to Canada so far because I am eligible to work there, and would like to settle there. However, without a stable job, this is difficult to be realized. I am curious: how can I overcome this limitation? For example, can I apply to positions in other countries, while I am not in those countries, physically, and not eligible to work there (I would need a work permit)?
 
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S_David said:
Right, but after a year of trying in the field of data science, my chances don't look good as well, so I am back to the thought whether it is a good idea to change careers or not. My citizenship and geographic location probably have a role. I have restricted myself to Canada so far because I am eligible to work there, and would like to settle there. However, without a stable job, this is difficult to be realized. I am curious: how can I overcome this limitation? For example, can I apply to positions in other countries, while I am not in those countries, physically, and not eligible to work there (I would need a work permit)?
The policies vary with each country. As far as the US goes, you can apply for a job in the US while you are not resident in the US. If an employer decides to hire you, it will need to sponsor you for the proper visa for you to enter the US and work for that employer. For an industry job, your chances are probably better with a large corporation, since they will have the HR and legal staff knowledgeable about the visa process and have the funds to pay for the associated fees. Another option is to pursue another postdoc in the US, which requires a different visa from an industry job. The whole visa situation in the US is in a state of flux right now, but a visa for a postdoc would likely be easier to get. If you were to postdoc at a top school such as MIT or Stanford, though, you'd likely have a good shot afterwards at getting a job with a major company (no guarantees of course; and the hiring company would need to sponsor you for the proper visa). In your situation, you have nothing to lose by applying for both industry and postdoc positions in the US, given that you haven't been able to land a job (wireless communications or data science) in Canada. So look for posts; but you will have better chances if your previous profs and colleagues have personal contacts in major US universities and companies.
 
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Others may know more about than me, but I would do a post-doc instead of doing nothing. As a hiring manager, I don't like to see gaps in people's resumes. Stay engaged with the field, contributing and doing something that you can, at the very least, turn into a bullet under "Employment History" in your resume.

The visa situation is a weird thing. I think that in general, companies in the US will hire you under the H1B category if they find your talent compelling. I would recommend that you at least give it a try. The odds are stacked against you because US universities churn out many, many, topnotch foreign students who are competing for the same H1B category and there is no reason for a US company to hire you versus a local person unless you are hot stuff. But it has happened - we have hired from both Canada and Europe because the candidate did something very specific in their PhD research that we were looking for.

However, your better bet may be to get a postdoc position in the US, versus an industrial position. That may be a bit easier to get and later when you are looking for industrial employment, you become, from the viewpoint of the hiring company, a local hire versus a "foreign" hire.
 
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S_David said:
Right, but after a year of trying in the field of data science, my chances don't look good as well, so I am back to the thought whether it is a good idea to change careers or not.
I'm confused too; you don't appear to have a career, so what is there to change? What jobs you apply for? Why not apply in both field? How many applications have you sent out in the past year? What sort of networking are you doing? It feels like you aren't casting a very wide net.

And are you fully unemployed right now? Being unemployed looks bad on an application, particularly in a good economy. You should get yourself a job - any job.
 
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  • #7
russ_watters said:
I'm confused too; you don't appear to have a career, so what is there to change? What jobs you apply for? Why not apply in both field? How many applications have you sent out in the past year? What sort of networking are you doing? It feels like you aren't casting a very wide net.

And are you fully unemployed right now? Being unemployed looks bad on an application, particularly in a good economy. You should get yourself a job - any job.

I meant whether to jump to the data science field and invest time on developing the skill set it requires, or to stay focused on my field and keep doing research. I have applied to all sorts of jobs in both fields: wireless communications and data science. The wireless communication field has very few opportunities, but I apply when I find a position. I have sent many applications (probably > 500). To be honest, networking is not my strongest asset yet. I need to work more on that. You are right, being unemployed looks very bad. Luckily I have another postdoc contract coming soon. I will try not to leave a gap again. Thanks
 
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Do you have a chance to get a postdoc position in the US? When you finish your postdoc contract, it will be a lot easier to apply for US jobs when you are physically in the country than when you are outside.
 
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Scrumhalf said:
Do you have a chance to get a postdoc position in the US? When you finish your postdoc contract, it will be a lot easier to apply for US jobs when you are physically in the country than when you are outside.

I haven't tried yet, but I think I have a better chance than in Canada, given the US has many more universities, and thus, I assume, more positions, and of course if getting a VISA is not difficult. I agree. Being physically present improves my chances in a given area. This is true, I think, even within Canada in other provinces. It seems that employers prefer local residents over others. Which is understandable, especially if there is no shortage of experience locally and/or other candidates don't have enough experience (so, why to bother with them administratively). Thanks
 

1. Should I switch careers to data science if I have no prior experience in the field?

It is possible to switch careers to data science without prior experience, but it will require dedication and hard work. You may need to invest time and resources into learning the necessary skills through courses or self-study, and gaining hands-on experience through projects or internships.

2. What skills do I need to have in order to be successful in data science?

In addition to technical skills such as programming, statistics, and data analysis, successful data scientists also possess strong critical thinking, problem-solving, and communication skills. They also have a passion for learning and a curiosity for exploring and finding insights in data.

3. Will switching to a career in data science be financially beneficial?

Data science is a rapidly growing field and is in high demand in various industries. This demand for skilled data scientists often translates into competitive salaries and benefits. However, the financial benefits will also depend on your skills, experience, and the specific job you pursue.

4. Is it necessary to have a degree in data science to switch careers?

While a degree in data science or a related field can be beneficial, it is not always necessary. Many successful data scientists come from diverse educational backgrounds and have learned the necessary skills through self-study or practical experience. Employers often value skills and experience over specific degrees.

5. What are some potential challenges I may face when switching to a career in data science?

Some potential challenges you may face when switching to a career in data science include the need to learn new technical skills, competition for jobs in the field, and potential resistance from employers who may prefer candidates with traditional data science degrees. It is important to be prepared to work hard and constantly upskill to stay competitive in the field.

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