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Two years ago, I came to the US to start my Master’s degree in Economics. After the first year, I was fortunate to earn a summer internship in a big tech firm as a Data Analytics intern. With good education and background, I was completely confident in earning a full-time role as a Data Analyst after graduation. I started applying intensively from February: creating a hit list of roles and companies that I want, networking with alumni and people from those firms, and preparing for interviews.
Then, the pandemic came. In March, all of the roles that I applied were canceled. The job market was more crowded than ever with a decrease in demands and an increase in supplies. Companies downsized and laid off their employees. A lot of talents became available in the job market. My job search journey suddenly became much longer than I expected. Experiencing the endless job search process, receiving rejections, and being burned out from multiple interviews every week made me feel hopeless.
After months of persistently applying, finally I earned a full-time Data Analyst role at a start-up in Boston, where I have an opportunity to do exactly what I love. In retrospect, there were three main lessons that I wanted to share to help you go through this trying time.

Networking, networking, and networking
Let’s think about the applying experience that you had. You opened LinkedIn, saw a Data Analyst job post from the firm that you like, and decided to apply. You spent half an hour to tailor your resume, half an hour to write a compelling cover letter, and another half an hour to fill in the application. And what happens next? Nothing. You just simply didn’t hear back from the firm. Two months later, you received an email with the subject "Thank you for applying to [company name]" and with the familiar message: "We are very impressed with your qualifications; however, we have decided not to move forward with your candidacy for this role".
This story seems to be so familiar with all of us. So, how could we do differently? Networking. Instead of spending an hour and a half to apply, let’s spend that amount of time to do networking. Networking is a great way to get through the door. Chances are you will be connected to the recruiter or the hiring manager of the role. If not, staying in the referral pipeline tremendously helps too. So, how would you go about it?
There were two sources of contact that you can find: alumni from your school and LinkedIn contacts. Each source has its pros and cons. Talking to alumni is great because your similar background (coming from the same school) means a lot. Generally, alumni want to help the next generation. There are potentially a lot of things you can talk about regarding your common learning experiences. However, you might not find any alum currently working at the firm you want to apply to. The alum you know might work at a completely different department that has little contact with the team you are applying. If that is the case, you may want to try messaging relevant LinkedIn contacts. Although they have little incentive to help you as you and they are strangers, they might have direct access to the team that you are interested in. So, what strategy you should use? The answer is both.
A low-hanging fruit step to find alumni contacts is reaching out to the Career Center of your university. They may have a list of alumni who are willing to help students. My university has an alumni database where their emails are visible. Once I have a list of alumni that I want to reach out with their contacts, I emailed them. Sending emails is a good way to get their attention. Your email may pop up right away in front of them, your message can be longer, and you can attach your resume to your email. Alternatively, you can connect them on LinkedIn and send an introduction message.
If the first strategy is not possible or not helpful, here is how I search for strangers on LinkedIn. On the People search, I filtered by Current companies (the company that you are applying) and Locations (the US, in case those companies have offices outside the US). On the search box, I typed the team or the title that might be relevant to the role. Among the results, I checked their profiles to create a list of who is relevant the most. Then, I sent connection requests with short and concise messages. It is always recommended to send a message besides the connection request and mention the exact role or team that you are applying to. However, do not mention about referrals from the very first email.
After the person accepted my connection request, I shared more with them about my background and interest in the company. If they are comfortable, I was opened about asking them to refer, introduce myself to the hiring manager, or pass my resume to the aligned recruiter. The same process applies to alumni. Being personally introduced to the hiring manager or having a referral increases your likelihood to kick-off the hiring process.
Prepare for technical interviews
As a Data Analyst candidate, I am sure that all of you know what to expect during the interview process. The skills vary across firms and exact roles; however, the following skills are normally expected: Excel, SQL, data visualization (E.g.: Tableau), and data analysis. Some firms might be interested in Python and machine learning too. Behavioral questions are definitely and sometimes equally important; however, I will leave this topic for another post because I want to focus more on data analyst interviewing aspects.
The first step is to prepare at least three stories about how you used Excel, SQL, or Tableau in the past. It is not strictly based on past work experiences; however, you should be able to tell the formulas or functions that you used, the complexity of the projects, and the impacts. Then, it is about practicing. For Excel, googling exercises and applying the formulas you want to practice should work. For SQL, I practiced on Leetcode. I set a schedule to practice daily with at least three to five questions a day. I spent a lot of time to think about the solutions, compare with peers’ answers, and write down what I can improve or what I can learn from the exercise. For data visualization, since all of my previous dashboards and visualizations belong to the companies that I worked for, I found public data sets and created two to three dashboards to showcase my skills.
Practicing data analysis problems is more tricky. Data analysis problems could be asked in two ways, either a general business question that requires you to break down the steps and bring a data-driven solution or a data case that asks you to crunch the data and share insights from that specific data set. The first type of data analysis problem depends a lot on the company that you are preparing for. For example, when I was applying to an e-commerce company, I did some research to learn more about the common business problems that they are facing and relevant metrics. I asked myself questions, such as how to improve the number of customers, how to increase the number of purchases, or how to reduce churn. I wrote down concise bullet points to organize my answers and practiced talking as if I were presenting the solution in front of the interviewer. For the second type of data analysis problem, I found public data sets (E.g.: Kaggle) and practiced crunching data: doing exploratory analysis, visualizing data distributions, finding correlations, and applying statistical methods to find insights from the data set.
Build your brand
You should expect to compete with hundreds or thousands of applicants for one role. Therefore, building your professional brand helps you stand out from the crowd. I made sure that recruiters and hiring managers could recognize my Data Analytics experiences by looking at my profile. All of my past experiences highlighted data analytics related aspects and achievements. My LinkedIn profile has all relevant keywords and skills that recruiters may search for or look for. I built a GitHub portfolio that shows past projects, both school, and personal ones. Besides, a personal website works as well.
Since tailoring your profile is important, I only applied for the roles that I was interested in. I carefully read the job description and noted down the skills and experiences that the team is looking for. Then, I compared the relevance between my resume and the job description. I tailored my experiences to closely match the requirements. For example, for a Marketing Data Analyst role, I emphasized my marketing related experiences, such as optimizing funnel conversion process, improving email performances, or conducting customer segmentation analysis.
Taking online courses and showing online certificates are also good ways to signal your skills and passion. I frequently learned online courses from Coursera and LinkedIn Learning about various data analytics related areas then showed the certificates on my LinkedIn profile. However, I do not recommend listing too many certificates on your resume. Your resume has limited space which should be optimized for important highlights of your skills and experiences.
A quick note
The job search process is stressful and frustrating. Therefore, I want to emphasize the importance of relaxing and balancing your life. There were times that I constantly found myself sending networking messages, practicing interviews, and feeling worried all the time. That does not work in the long term. Spending more time to prepare right before an important interview is acceptable; however, you will soon feel burn out if you cannot draw a clear line between a job application and other areas in your life.
During my job search period, I planned a clear schedule and determined how many hours I would spend on job search activities every day. I was also very serious about the hours spent on exercises, running, talking to family and friends, and hobbies.
I hope you have some concise takeaways from this article to help you achieve your goal soon. Wish you success in your job search.