7 Simple Tips from My Mid-Career Switch into Data Science
Some general tips to consider if you are thinking of a mid-career change into data science… or any other fields for that matter.
Making a mid-career switch is never an easy decision for anyone, let alone into a technical field like data science. It requires a great deal of reflection, contemplation, guidance, and courage, especially if you had started out in your original job expecting to go far and climb high.
At the same time, it should also not be surprising if you find yourself thinking of a mid-career switch. Let’s be honest — for most of us, career aspirations evolve with the stage of life we’re in.
It should, anyway.
At the start of your career, you’re young and energetic. You’re not afraid to stretch yourself and try different things.
When you start a family, other things begin to demand your time and energy — your spouse, extended family, kids. Understandably, you need to be more productive in the time you invest in work, or be more strategic in the kind of work you do.
Or, you could have your own motivations for gravitating towards the data science field.
These are all perfectly reasonable.
Well, one could even argue that switching between jobs should be a new normal in this digital age.
No matter what your story is, if you’re thinking of a mid-career switch, you’re definitely not alone. I made my mid-career switch from policing to data science last year and here’s my story:
Having gone through the process, I have the benefit of hindsight to reflect on what led me down this path and what gave me the conviction to do so.
In this post, I organise these reflections into 7 simple general tips that you should consider when making a mid-career switch into data science, or any other field for that matter.
Tips for a mid-career switch
1. Know yourself
First and foremost, you need to know yourself. You need to be crystal clear about what your life priorities are, what your current career goals are and whether those two are aligned.
Some questions you might want to ask yourself are:
- Are you still deriving satisfaction and meaning from your current job?
- Is your current job conducive for starting a family (assuming that’s what you want)?
- Are you still learning and growing in your current job?
- Do you see a long-term future in your current job?
If you are new to data science, you should also be clear whether your interest in data science is temporary and you’re happy just learning (i.e. what I like to call “leisure learning”), or you’re really serious about making it into a career. Give yourself some time to figure this out within yourself.
2. Talk to people
Once you’ve sorted out your priorities and career aspirations, you should talk about it to people you can trust— your spouse, family members, good friends. Tell them what you’re going through and ask them what they would do if they were in your shoes.
Hearing others’ views can give you fresh perspectives, which can in turn give you greater motivation and perhaps a nudge in the right direction.
It can also open up your eyes to alternatives that you’ve never considered before. Or, who knows, you may even be connected with the ‘right’ people who can unlock the doors to new opportunities for you.
3. Write your reasons down
Once you’ve made up your mind about making a career switch, the first thing I strongly recommend you to do is to put into writing, your reasons for doing this.
This can be in a form of a blog post, a tweet, an Instagram story, a Facebook post, or even a post-it in front of your desk. I did mine by writing the above reflection piece on Medium. This simple exercise can go a long way in helping you to crystallise your thoughts and motivations.
We are all humans and there may come a time in the future when you start having second thoughts about your decision. Is this really the right move for me? Is this the right time? Will I be qualified enough for the next job?
When these negative thoughts start creeping in, look back at what you’ve written. It can serve as a powerful reminder of why you made this decision. More importantly, it is to remind you that you are already past that decision point, so the only way is to look ahead and move forward.
4. Plan your finances
Let’s not kid ourselves. There is A LOT of preparation involved in making a successful career switch and figuring out how to get there. It requires time, discipline, focus and determination.
One of the most important things to plan for is your finances. Think about your monthly expenses — bills, house mortgage, loans, other necessities etc .— and whether you have enough savings to tide you through. This is especially critical if you’re having a break between careers, i.e. not having any income for a period of time.
Also, if you’re likely to get a pay cut in your next career, you should carefully evaluate whether you think that’s a worthwhile move, in exchange for the potential gain you’ll get in terms of job satisfaction.
5. Plan your learning roadmap
The other important aspect you need to plan is your learning roadmap, especially if you’re moving into a technical field like data science and you are new.
Almost certainly, you need to pick up new skills — Python, R, and SQL being the more common programming languages. It is also essential for you to learn other relevant topics such as statistics, machine learning, and deep learning.
There are plenty of online learning platforms — Coursera, Udemy, Datacamp, Dataquest, Codecademy, Leetcode etc — and you can’t possibly do everything. So, you really need to plan and prioritise which courses to invest your time in.
You should also plan for and set aside time to do personal side projects or Kaggle competitions. This is to give your potential recruiters some level of assurance that although you’re switching from a different career, you’re not totally inexperienced in data science.
It is not my intention to prescribe a roadmap for learning data science in this post, but here are some nice resources you can check out:
- A Brief Guide to Effective Learning in Data Science, by Tan Pengshi Alvin
- How to Learn Data Science for Free, by Rebecca Vickery
- How to Learn Data Science Online: ALL You Need to Know by Lianne & Justin @ Just into Data
Besides finances and learning journey, there may be other factors you should consider. It is not possible for me list them out here and after all, it’s likely that you would have factors unique to your own circumstances.
The bottom line is, make sure you plan and prepare yourself well.
“Planning is bringing the future into the present so that you can do something about it now.” — Alan Lakein
6. Take the dive
Once you think you’re about 50–70% ready, go for it. Put up a decent resume, shortlist jobs you wish to apply for and start making those applications.
Don’t be too stressed up if you feel like you haven’t “checked all boxes”. It’s almost impossible to do that anyway.
“The truth about job posts is that they are not always written by hiring managers, sometimes they are generic and outdated. Don’t self reject. Let the market decides”. — Daliana Liu on LinkedIn
Put yourself through the interview processes and don’t take things too seriously. Take the first couple of interviews as a learning process. You’ll most likely discover what recruiters are typically looking out for, and where your knowledge gaps are.
For example, if an interview process includes a live programming test in SQL, an area you know you’re weak in, you may compromise that interview but at least you know that’s something you need to work harder on for future interviews.
7. Expect the unexpected
Through out your career transition, don’t expect things to be smooth-sailing either. There will be bumps along the way. You may not get shortlisted for interviews. You may fail certain some technical assessments. You may perform poorly during an interview and end up throwing away your chances.
That’s why it is important that right from the start, we prepare ourselves for unexpected events. By doing so, we prime our minds to respond more effectively to failures.
“Always expect the unexpected, so that when the unexpected happens, it will be less unexpected.”
Be bold, be daring and always adopt a positive mindset. Believe in yourself. Trust that when one door closes, another one will open.
Final thoughts
All too often, we find ourselves hesitant to leave our careers, even though there are red flags. That’s perfectly fine. Everyone’s circumstance is unique, so to each his own.
I also do not advocate switching careers the moment there is the slightest unhappiness in your job. That wouldn’t be ideal either. You should always put in the effort to press on and make things work.
However, if you find that your experience, skills, and aspirations can lead elsewhere, then a career switch might just be that spark you need to rejuvenate your energy and passion.
If you are considering a career switch, I hope these tips have been helpful for you, particularly if you’re thinking of going into data science.
Whichever field you decide to switch careers to, my parting advice would be this: Once you’ve made that decision to make a mid-career switch, never regret it. Remind yourself of why you did this in the first place and keep looking ahead!
All the best!
That’s all for now. Thanks for reading this post! If you’ve found this post useful, do let me know in the comments. I always find it inspiring to hear about others’ stories of mid-career change, so if you have a similar story to share, I’ll be really interested to know. Feel free to follow me on Medium or reach out to me via LinkedIn or Twitter. Have a great day!
