Hey guys.
Welcome back to my channel.
Today, I want to tell you a story about myself:
how I went from being a civil engineering master's student
to becoming a six figure data scientist.
It was an incredible six month journey
and I learned a lot along the way.
The reason I choose this story to share with you today is
because the current job market is really tough
for people who are looking
for their first data scientist job
and I wish I could offer some encouragement
by sharing my own story with you.
I know one common frustration is
that companies want experienced data scientists
and most job posts require years of experience.
But if you are looking for your very first data scientist job
you will face the chicken and egg problem.
You cannot get hired without experience and you
cannot get experience if you cannot get hired.
This is definitely a vicious cycle
so I want to share with you how I overcame that.
I believe that with the right direction and hard work
anyone can achieve their dreams.
I know this because I've done it myself.
So let me share with you how I got started.
I began my data science journey about seven years ago
in 2016 when I had only one semester left
for my civil engineering master's degree.
My specialization was in transportation engineering.
I had some relevant skills.
For instance, I was proficient
in Python, statistics, SQL, and GitHub.
These skills were honed during my research
in the transportation engineering department.
I worked with a couple professors
in the Department of Aviation Research
and got opportunities to clean up a large amount
of flight trajectory data and build models using the data.
However, I never had any internships
or work experience in data science.
Now, you might be thinking, "Why is someone without a degree
in data science nor any work experience or internship
in the field interested in finding a job in data science?"
Well, I was inspired by the PhD students I was doing research
with, who all wanted a job in tech.
As I explored the world of tech
I began to see its potential for innovation and impact.
I realized that technology is not just a tool
but a way to create change in the world.
I felt compelled to be a part of that change to
use my skills and knowledge to make a difference.
For example, I was really interested
in the products that Uber and Lyft have developed.
They have made people's lives so much easier
and more convenient
by revolutionizing the transportation industry.
I also admire how companies like SpaceX
and Blue Origin are pushing the boundaries
of space exploration
and making it more accessible for future generations.
I loved the idea of creating something new
and using data to solve problems that had never
been solved before.
I was driven by the challenge of working
with data and the potential of using it to
unlock insights that could transform people's lives
and for me to be a part of the change
I need to find a job in tech.
But what was particularly discouraging was that none
of my fellow master students were able to get a job
as a data scientist.
After speaking to my peers
and two professors in the department, I learned
that no one from the same master's program had
landed a data science job before,
so I was worried about my irrelevant educational background
and how I could land a job
in a completely different industry.
I decided to get started anyway because I only
had one semester left and I needed to find a job.
After I made the decision to find a data scientist job
I started browsing job posts.
I quickly faced two major obstacles.
First, I didn't have all the required skills, such
as machine learning, data pipelines, ETL, et cetera.
I had never taken any machine learning courses in school
so I searched for some courses online
and tried to build my skill set
by consuming as many online courses as I could.
It seemed that there were plenty
of resources out there that could help me bridge the gap.
At the end of the day
you can always acquire more skills if you want
right? However, these skills were not enough.
The second obstacle was completely out of my control
and it seemed impossible to overcome.
It was pretty hard for me to land interviews.
I spent a lot of time crafting my resume,
asked more than 10 people to review it and give me feedback,
and spent numerous hours writing cover letters
for different positions.
After sending out 500 applications in the first three months
all I got were rejections.
I did not get any interviews from any company.
I was worried
that I was going to spend a few months job searching
and still be jobless after graduation.
As I was working with a professor on a research project,
his former PhD student
and a current alum whom I also knew and had met in the past
came in to visit and say hi to everyone.
She was an Applied Scientist at Amazon.
It was very fortunate for me
because I had the opportunity to talk with her,
share my concerns, and ask for some advice.
I told her that I had been job searching
for quite a few months and felt stuck.
Actually, I was feeling like giving up
because it was really hard for me to land interviews
and without an interview, how could I land a job?
Also, I didn't have all the skills required
for a data scientist job.
After speaking with her, she eventually became my mentor
for which I am very thankful.
It was a momentous help for me to land a job
and become a data scientist.
I am still thankful to this day that I was able to
get guidance from a more experienced professional and
without it, I'm not sure how long it would have taken
or where I would be today.
So she agreed to meet with me every two weeks
for a one hour mentorship session, and those sessions
were invaluable.
Specifically, there were three things she helped me
with that have been game changers.
First, she pointed out many of the misconceptions
I had cultivated by consuming information online, such
as the belief that writing great cover letters is important.
So I used to spend a lot
of time writing them along with my job applications.
She told me it was a huge waste of my time
as many recruiters don't even look
at the cover letter due to the high volume of applications.
This single piece of advice saved me a ton of time.
Also, I used to be very shy
about reaching out to recruiters and hiring managers.
I did not know what to say, and if they didn't respond
I didn't know what to do.
She helped me review my messages, and she told me
that it's not realistic to expect everyone to reply
to me immediately.
It's important to follow up
with recruiters and hiring managers consistently
to show my interest and persistence.
You know what?
That's actually how I eventually
got some interview opportunities.
Secondly, she reviewed my study plan so
that I could focus on what was most important
and not waste time studying anything irrelevant
to landing a data scientist job.
For example, I was taking some computer science
algorithm courses to enhance my software engineering skills
and she told me that it was not super relevant
to data science, so I knew where to spend my time
on things that are most relevant.
Lastly, she shared with me lots of tips to prepare
for interviews and what I need to pay attention
to when talking to potential employers.
For example, she taught me how to engage
with the interviewer during our conversation
and how to provide a structured answer
during interviews to demonstrate my thought process.
Working with a mentor or coach has been so effective
especially in this day and age.
No matter how much research I did
it did not come close to being as useful
as actually speaking to someone who has experience.
Because as much as you can Google
or ask ChatGPT, everyone keeps giving conflicting advice.
One website says cover letters are really important to show
that you have the initiative to set yourself apart
and explain who you are.
While another guru tells you
that it's actually a big waste of time.
So having someone with experience can really
help you get your foot in the door.
This way, you can learn
about the real situation instead of relying on whatever is
on the internet or on classically giving advice
which may not be suitable for you.
Now, let's talk about the results of my journey.
After submitting over 800 applications
for data scientist positions
including raw applications, referrals, and cold emails
this effort led to five interviews
and ultimately two job offers.
I was so excited
that I landed my first six figure data scientist job
as a civil engineering master's graduate.
In the end, I decided to become a data scientist
for a supply chain management startup.
It was a promising company with over 400 employees
building a supply chain management product.
What was amazing about the interview process
with this particular company was
that they hired me on the spot.
During the onsite interview
they were supposed to be five rounds of interviews
but after the very first round of interview, a presentation,
the VP told me I was hired
and I could take the rest of the interview easy.
I was so relieved because I had been searching
for six months until that moment
and I can tell you I could not have achieved
that without my mentor's help.
Before the onsite interview
she helped me with improving my presentation
in two mentorship or coaching sessions.
She listened to my presentation, asked me questions,
and gave me suggestions to improve
both my slide deck and my communication.
Another thing that was really helpful was that she pointed
out that showing up confidently in interviews
especially for onsite interviews is really important.
But you know, I was super insecure, right?
I wanted to land a job
in an industry that is totally different
from what I had been studying in school.
However, she told me how to leverage the skills
I already have to impress future employers.
For example
this supply chain management company was really looking
for someone who knows about transportation
and my specialization
in school was transportation engineering.
So my mentor actually told me
that I should showcase my strengths and how I can contribute
to the company because of my training in transportation
and not be too worried about my weaknesses or limitations.
The company cares most about whether you can contribute
or not rather than your educational background.
So the mindset shift as well
as the practice we've done together was a key
for me to deliver a killer presentation
and get hired on the spot.
I cannot thank her enough for her guidance.
My mentor became a Principal Applied Scientist at Amazon
and we still have a very good relationship to this day.
I continue to learn a lot from her
and I really appreciate her guidance and mentorship.
Finally, I'd love to share some takeaways with you.
I'm really thankful for my mentor because the
difference between the first three months of my job
search and the other three month after I met her was huge.
In the first three months
I spent a lot of time searching on Google
and I still didn't know whether I was on the right track.
It was a big waste of time
and I felt like I was getting nowhere.
During the second half of my job search journey
my mentor provided guidance that helped me
accelerate the process and the result: I secured
five interviews and received two job offers.
Having someone who knew the inner workings
of the industry was crucial in getting my foot in the door.
Despite my extensive self research, even just one sit
down with my mentor was more helpful than anything else.
Also, I realized that I don't have to do this all by myself.
It's a journey that doesn't have to be taken alone.
It's great to have someone to encourage you,
give you direction, let you know
that you are on the right track
that you are spending your time on the right things
and show you what you can do to improve your process.
I also realized the importance of investing
in mentors or coaches who can provide the support you need.
I'm very thankful that I invested in myself
and had a lot of support from my mentor.
I was really lucky.
Even to this day
I invest in coaches and mentors in every aspect of my life.
Believe it or not, I have a communication coach to
help me improve my communication
in my YouTube videos and work with my team members.
I also have a health coach who helps me improve my health
and strength training, making me feel stronger.
I love working with professionals.
So that's my story
from a civil engineering student to a data scientist.
Thank you so much for joining me today
on this journey of transformation and growth.
I hope you find it inspiring.
If you are an aspiring data scientist
with no experience in data science, don't be discouraged.
It's never too late to make a change
and please let my story be an example for you.
Also, remember to ask for help when you need it.
You don't need to do this alone.
If you can find someone with experience in the field
it will be great
if you could connect with them and get some guidance.
Very likely you'll achieve the result you want sooner
and easier than you thought.
Thank you so much for being here and listening to my story.
Don't forget to like, share, and subscribe
for more stories and content on data science career advice.
I wish you a great day, a great career,
and a great life ahead.
I will see you soon.
Bye guys.