How can Project Managers transition into Data Science Roles? | Ep #27

Are you a Project Manager applying for Data Science Roles?

Join Manav in Episode 27 of Data Science & AI Weekly as he talks about how to smoothly transition from a Project Manager to a Data Scientist.

TIME-STAMPED SHOW NOTES:

[00:20] Topic of Discussion: How can Project Managers transition into Data Science Roles?
[00:23] Podcast Series Introduction
[00:46] Why do Project Managers upskill?
[01:58] Identify areas of focus in Data Science
[03:01] Level of hands-on Data Science to deal with
[04:29] Search for Data Science roles outside your comfort zone
[05:32] 3 To-Dos to ensure smoother transitions
[05:48] Wrap Up!
[06:02] Learn more about Data Science at www.accredian.com

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Are you a Project Manager looking to transition into a Data Science role?

Hi, everyone. Welcome to Episode 27 of Data Science and AI Weekly.

My name is Manav and this is a very exciting episode because in this episode, I’m going to discuss how can you as a Project Manager transition into a Data Science role successfully?

And can you transition in the first place?

Let’s get started. So we get a lot of Project Managers for our programs. And one of the reasons why most Project Managers are upskilling right now in Data Science and AI is-

1. They feel that their career has somehow stagnated
2. They feel that they want to be more relevant and their current competency or skill set is not relevant to the requirement that the IT industry has right now
3. They want faster career progression and they know that if they don’t take those steps now to improve their skills, they will not break into the top management tiers and that’s what your goal is.

And if you can relate to any of these three reasons, let me know, in the chat/in the comment section as well.

So those are perfectly valid reasons. And as IT professionals, what I always say is that no matter whether you are a Project Manager, or you are a Director or Vice President, you need to be on top of what the new technology trends are.

And the same is true for you, as you look to transition into Data Science roles. So here’s my advice for you as you plan to do that.

Number one thing that I would want from you is that as you look to transition, you need to identify what area of focus would you have in Data Science? Are you looking to become a generic Data Scientist? Or are you looking to become a Data Scientist focused in a particular field?

And that’s why you will need to see what is your current industry that you are currently managing projects of?

For example, you might be working in IBM and you might be working as a Project Manager for BFSI projects, right?

Let’s say Citibank. So you would want to maybe focus on Data Science and take the BFSI projects and work during the program on as many BFSI projects as possible and make them. That’s why that connection from BFSI to Data Science in BFSI is going to be very easy for you.

And that’s what the top management expects from you that you will be leading new and innovative projects. That’s the first thing.

The second thing that you will need to watch out for is that what level of hands-on Data Science you want to do, which means some of you might be hands-on, hands-on with programming as Project Managers, and you’d be comfortable, some of you would have left programming for some time, and some of you would have never done programming.

So there are three of these categories. And you will need to identify from a Data Science perspective, what do you want to do, for example, if you are a hands-on Project Manager, you can deep dive more into Python, and you should look to build good hands-on skills as well.

But if you know that Python or programming is not something that you are that strong in, you should still learn Python; be comfortable with it, but no need to go into the depths of programming.

Rather what you should be focusing on is the business outcome and what you should be doing is you should be looking at the application of Data Science in different industries.

So you should be asking the bigger picture, right and that’s what you should look at
whether you have that interest and background in programming and depending on that you should focus on one of these two areas.

The last and the very important question that you should be answering, as you look to transition is that am I ready to go out of my comfort zone to get Data Science roles?

Now, what you’d be surprised by is that your company most likely, no matter whether you work in TCS, CTS, Microsoft or JP Morgan is taking a Data Science initiative, your goal should be to reach out to your supervisors or reach out to your VPs or Presidents and try to find out where are these projects and at least talk to Project Managers who are leading those pilot projects, you will need to build that rapport because with 15 or 20 years of experience, do not expect an entry level job and that’s what you should actually not be aiming for.

And if you have that network with you, it will help make your job transition much, much, much smoother!

And trust me, I have seen it happening 10s of times with our students who are just like you Project Managers with 12-15-20 years of experience, right?

So it’s definitely very much possible. You need to have the right framework, you need to have the right strategy, you need to have the right mentors, if you have a combination of these plus, combined with your effort and sincerity towards progressing forward in your career, transitioning into Data Science and Machine Learning roles is absolutely achievable.

Right. So this is Episode 27 of Data Science and AI Weekly. I hope you loved this episode, let me know if you’re a Project Manager and if this video has helped you and if you have any questions beyond that, let me know that as well in the comment section.

Thank you for watching and see you in Episode 28!