【TMR internship】Some Reflection on My Life in TMR

On my final day of winter vacation, after having a deep conversation with some of my colleagues, knowing their perspective about the job, I feel like spending some time writing down some reflection about my internship. It’s not a formal introduction on what we do in our daily work, but more about my feelings on the job, on my growth and on what I still lack.

I tried to answer the question first: Who is suitable for Taiwan Marketing Research? Not so sure about this question, but I tried to conclude in a few points.

Who is suitable?

1. The one who doesn’t have much experience in data analysis but want to find a data-related intern.

I myself is a good example. By the time I started this internship, I can’t even tell the difference between the two mostly used module in data cleaning: Pandas and NumPy. Actually, during my interview, the company owner clearly pointed out that instead of data process proficiency, what they care more is the personality and attitude of an intern candidate. Then what kind of attitude they wish we have? Let’s come to the second point.

2. The one who prioritizes accomplishing the assignments over other duties in everyday life, including schoolwork and leisure.

I’ve been here for four months. During these days, there are many times I put off the homework due in next week or gave up friend’s party I was about to go just because of an unexpected task, not to mention staying up later and later to meet the deadline. I learnt how to discipline myself and manage my time so as not to sacrifice too much of my private life and tackle all the things in order. After all, we have to do everything in time.

3. The one who can adapt to fast-paced work environment and wants to be on a steep learning curve.

As mentioned before, I had difficulties using data analysis module such as Pandas and NumPy. Not knowing it’s because of Kaggle side project every week, the exams every month, or the project in progress, my capability expanded a lot. I learnt web-crawling, clustering, and data cleaning from these implementations.

Who is not suitable?

1. The one who can’t tolerate doing tedious works.

From time to time, we are assigned tasks that’s not that interesting or inspiring. For example, modifying ppt or covert “.py” to “.ipynb”. Once, I was asked to watch three three-hour-long videos and operate as what it does. The video consisted of numerous unfamiliar technical terms like “mongodb” or “heroku” that I don’t even know its usage. That was a painful experience both to me and to a more experienced colleague who taught me when I encountered any problem, which is almost every one or two hours.

2. The one who considers working as an unpaid intern unacceptable.

Of all the projects I engaged in, I’ve never been paid. As far as I know, only when we finish the training program and pass all the examination will there be any payment for these projects.

Challenges

About the job itself

For me, the most challenging part is about timeliness. There was never ample time even for a workaholic like me. In order not to feel too unfair when watching friends hanging out while I have to work, I constantly adjusted myself and reminded myself how these efforts can bring to me. The autohypnosis effectively helped me indulge on my own works.

About people

“All problems are interpersonal relationship problems.” There is no exception at work. Doing things by myself is one thing, requiring others to do is quite another. Once, my workmate and I were assigned some works during the Chinese New Year. I didn’t feel anything wrong at first because frankly, I didn’t have any other more interesting things to do. My workmate was totally different. She complaint and was surprised by my indifference. In the end, she unwillingly surrendered because she didn’t want to see me working by myself. Sometimes, it’s really hard to say who’s right and who’s wrong, or what’s more important and what’s not. One day if I have the chance to manage a project, I would keep this experience in mind and try my best to balance schedule of the project and workload of my coworkers.

Make a toast at year-end party

Lessons Learnt Along the Way

After learning about the job function of data scientists in my sophomore year, I’ve wanted to try it. The internship experience gave me a general view of how a data scientist’s life looks like, especially in terms of time allocation. Take the sentence for example: “Data scientists spend 80% of their time cleaning data rather than creating insights.” I couldn’t understand what it meant before, but feel strong resonance with it now. Realizing that data scientist is not far from my imagination and I do like this job, I know that I am on the right road.

Apart from technical skill improvement and career exploration, I also understand myself better. Cooperating with coworkers and communicating with supervisor confirmed me in my current understanding about myself. First of all, I am a workaholic. I would happily indulge my self in work for hours and ignore any other things as long as they are not emergent, even during the Chinese New Year. Second, I tend to look on the bright side of things. Some of my colleague gossiped about how clever our boss is to treat us as free labor and take our work for commercial use. Sometimes I did complain with them, but generally, I focused more on the online learning materials and real-world collaboration chances our boss provided and encouraged us to take.

For me, TMR is full of treasure and wait for me to uncover. By pushing myself to limit and utilizing the resources as best as I can, I grew closer and closer to the ideal image of “future me” in my mind. I am satisfied with my progress in presentation, communication, and data processing skills. For the rest of my life in TMR, I want to challenge myself further to wholly take the lead of a project. Right now, leadership is the quality I lack the most. As long as I catch up on the weakness, my interpersonal skill will be upgraded yet another level.

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