Amelia Hardjasa is a Data Engineer in Alloy's Vancouver office. Previously, she has worked as a data scientist at several different companies, including Boeing Vancouver and Pulse Energy. She holds an MSc from the University of British Columbia.
1. Why did you join Alloy?
There were two major factors that led to me choosing Alloy over other positions I was weighing at the time. Firstly, speaking as a data scientist, the data we have to work with at Alloy and the potential value we can create from it — in-depth descriptive analytics, prediction of demand and shortages, and prescriptive actions — are very exciting. Secondly, speaking as a person, I was very impressed by the professionalism, sincerity, and kindness I experienced throughout the interview process, and I leapt at the chance to work with colleagues like these.
2. What do you do at Alloy?
I’m a data engineer in title, and in practice that means I dabble in a variety of different parts of our backend. I spend a decent chunk of time working on our pipeline for ingesting and transforming data, but I also have the opportunity to work on more advanced analytics and machine learning projects, like demand forecasting.
3. What advice would you give to someone interested in a similar career?
I would definitely second my colleague Iva and highly recommend any internships you can get your hands on. They are one of the best ways I can think of to get your feet wet in a welcoming environment where you’re not expected to already know everything. Also, every company does things in a slightly different way, and being exposed to a variety of perspectives is a good way to avoid the trap of “when all you have is a hammer, everything looks like a nail.”
Another thing I would recommend, especially to engineers from disadvantaged or minority backgrounds, is not to pre-disqualify yourself from jobs you’re interested in. A Harvard Business Review article noted that, commonly, “Men apply for a job when they meet only 60% of the qualifications, but women apply only if they meet 100% of them.” Writing job descriptions is difficult, and a lot of the time what is posted as a “requirement” is more of a “nice-to-have.” I wish I had realized that earlier in my career and been more open to exploring positions that I wasn’t 100%+ qualified for.
4. What first interested you in data science?
I have a somewhat less traditional background than most other software engineers I’ve worked with. I sort of “fell” into data science — I took a part-time position doing data entry and the data scientists I was working with encouraged my interests when I wanted to automate some of the work. Compared to biology, the field I started in, the impact of your work is much more tangible and immediate, which I find very rewarding. That said, a lot of the foundational skills I developed as a life scientist have a great deal of applicability to the challenges I face when doing work in data science and machine learning.
5. How would you describe the culture at Alloy?
In the time since I’ve been at Alloy, one thing I’ve really appreciated in the people I interact with is that they’re all very sincere and dedicated to the work they do. I feel that we all have a common goal in making a product that’s of high quality and valuable to our users, and that sense of shared purpose is very important to me.
6. What do you like to do outside of the office?
I like to play a variety of board games and video games, and for the brief span of time in Vancouver when the weather is nice, I very much enjoy sea kayaking — we have a lot of sheltered waters and it’s a great way to interact with West Coast wildlife. The thing I spend the most time on outside of the office, though, is probably fostering semi-feral cats and kittens with the Vancouver Orphan Kitten Rescue Association. If you’re in the area and looking for a pet, check out all the adorable cats we have available to adopt!