Before switching my career to data science, I was in the engineering field. I received a BS and MS degree in Biomedical Engineering and Optics/Optical Engineering from the University of Rochester (UR) in the US. During my study, research and internships, I extensively implemented algorithms, ran simulations, and did statistical and image analysis by coding in MATLAB, which triggered my interest in programming and to dig more into AI and machine learning. I decided to pursue my interest by entering a data science master’s program at UR; the training and practice in various topics further encouraged me to pursue a career in this field. From August 2020 to January 2021, I participated in WeCloudData’s project-based program to gain more hands-on experience in tackling real-world data science problems. After then, I joined Chapeau! AI agency as a data scientist, where I work on AI product development.
My Motivation to Join the Project-Based Program at WeCloudData
After graduating from the Data Science MS program at UR in December 2019, I moved to Toronto with my family in early 2020. With an excellent academic record from one of the top universities as well as a handful of internship experience in industrial settings, I thought it would be easy for me to find a job. However, things went very differently when I started my job search. From February to July 2020, I had applied to over 100 positions but heard no response from most of them. The ones that did take interest in my resume did not proceed with me beyond interviews. I was very confused and frustrated after such an extended period of job hunting and started to think about what might be wrong. After some research, I realized there were several factors that lead to this situation:
First of all, the COVID-19 pandemic has greatly impacted the job market. Before the pandemic, there were many more open positions, but when the pandemic hit, most companies either froze their hiring process or completely cut the positions. For the remaining ones, the competition became intense: not only did the number of applicants surge over hundreds or even thousands for one position, but the fresh graduates had to face against the experienced for even entry-level positions.
Second, I went to school in the US but decided to start my career in Canada, which brought challenges as well. No Canadian employers were coming across the border to any job fair at my school and there weren’t many alumni in Canada, so it was difficult for me to build a career network and get referrals. On the other hand, universities in the US are less recognized in Canada, and the internships that I had in the US weren’t helpful: these companies did not provide direct hires in different countries, so these factors built up the challenges for a new Canadian plus fresh graduate to land a job.
What was even worse was that the longer I was unemployed, the more difficult my job search became as employers do not like career gaps. They prefer candidates who keep themselves busy and stay in a competitive environment compared to those who are unemployed for 6 months.
At that time, I found WeCloudData on Meetup and went to the career talks and events tailored for data professionals. After talking to Shaohua and a couple of other mentors from WeCloudData, I decided to join the project-based program to refresh my data science knowledge, practice my skills even more, and get some guidance and help from the professionals in my job search.
How Has the Program Helped Me
As a fresh graduate from the Data Science MS program, my knowledge and skills were qualified for many data jobs, so I did not need to start from the very basics like most Bootcamp students. After doing WeCloudData’s qualification exam, I was assigned to the project-based program.
The project-based program did not mean that I could only work on the projects. In fact, it went so much beyond my expectation of how many learning materials I would get access to, to not only refresh my knowledge but also to learn more skills. At the very basic level, I had access to courses that the Bootcamp students took, so I could go back and look up anything that I felt uncertain about. I was also free to join the part-time courses to learn more about advanced topics, such as big data, which was not offered back in my data science MS program. All of the courses were very practical and meant to prepare the students for their careers, so it was quite a different but enjoyable experience for me compared to those offered in the universities that lean more towards academics.
The project experience was really helpful as well. I had worked on two different projects during the program. Both of them were team-based and led by an experienced product manager. The project experience not only allowed me to practice my data science skills and expand my resume, but most importantly, I was able to work in a collaborative environment with my teammates and worked closely with the clients. In this program, we were getting our hands dirty to solve real-world problems, and it prepared me for the challenges I currently face in my job as a data scientist. Within the team, we extensively used agile project management tools like Jira and Confluence to keep track of the project progress, and also used version control software like GitHub to collaborate on programs; with clients, we hosted regular meetings and made presentations to either give updates or to further discuss the project scope. Compared to university programs, this project-based program also focused on soft skills, so one of my greatest gains from it is that I became more comfortable in communicating with stakeholders in any data science related projects.
Of course, the most direct benefit that I got from this program was successfully landing a job. The program offers a variety of career services including resume/cover letter review, mock interview, and job referrals. In fact, my current job at Chapeau! AI Agency was referred to me through the program. Besides the referral, I was given advice on interviews, case studies, and even offer negotiations by the mentors during my application processes. Everything went much smoother compared to what I experienced before joining the program, and I successfully landed my current job after struggling through a long battle of job hunting.
My Advice for New Students
For anyone who is having a difficult time finding a job in the data science field, or wants to switch their career path, here is some advice for you. I have been through all of this, and I know how despairing it is when things don’t align with your expectations.
First, you do not need to face everything alone. I started the job search by myself, but it turned out to be not as efficient as having some help from the professionals. Sometimes, it is difficult to find errors in your resume or bad habits in interviews, but these can be easily pointed out after a resume review or a mock interview. It is also beneficial to keep in touch with your peers who share similar experiences and interests. You can learn from each other, collaborate on side projects, or share stories of things that happened during the interviews.
Last but not least, even if you keep failing in your job search, do not give up. There will always be something new waiting for you, so what you need to do is to better prepare yourself. Go ahead and expand your knowledge on new topics, learn a couple of new skills, do a side project that you’re interested in, or join communities to stay informed of new technologies. These will all help you stay sharp and competitive in the job market, so when there is a new opportunity coming up, you can be sure that it will not slip through your fingers as easily.