Category : Tech

Mobile Monday @ Tagged: Women Who Code

Tagged promotes diversity both at our company and also in the broader tech industry. We’re always looking to partner with groups that share this goal, so last week we were proud to welcome Women Who Code to our HQ.

A small group of women joined us for a mobile study group, which was part of a three-session sprint for Android development bootcamp. This is a relatively fast-paced course that touches on several essential parts of Android development.

By the end of the class, attendees knew how to finish writing a simple To-Do-List application, so they were able to learn how to modify layout files to update application UI, implement a ListView widget with an ArrayAdapter and add keyboard listeners in an Activity for EditText objects. As a bonus, the instructor demonstrated how to add one additional line of code to show a toast message in-app!

The hands-on, step-by-step approach of the class made each piece of code much easier to understand. I’m sure by the time we were done, many attendees were already thinking of ways to make the application look fresher and run smoother. In the next session they’ll be learning to use content providers, local cache/database and intent services to make the To-Do-List application even better. Way to go ladies!

Ilona Sheynkman contributed to this post.

Haiyan Wu

Hayain Wu is a Software Engineer II on the mobile team at Tagged.

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Takeaways from SBP14

I recently attended the 2014 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction in Washington, D.C., where I learned various ways of modeling and making predictions with social-science and social network related problems. Here are some papers that were presented during the conference that I found relevant to Tagged:

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Dai Li

Dai Li is a Data Scientist I on the relevance team at Tagged.

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Women in Data Science Meetup @ Tagged

Tagged recently hosted a Women in Data Science meetup featuring several lightning tech talks and a panel discussion. As a data scientist on the relevance team at Tagged, I had the pleasure of speaking on the panel with other influential women in this field.

I joined Vivienne Ming, Chief Data Scientist at Gild, and Debora Donato, Principal Data Scientist at StumbleUpon, on the panel. First, we talked about the qualifications of a data scientist. While data scientists are expected to possess certain technical skills (coding competence in Python/R, proficiency with SQL, familiarity with machine learning algorithms and basic statistics), often more important are general problem-solving skills, persistent intellectual curiosity and the ability and eagerness to learn new things. Furthermore, as data scientists often work closely with product and engineering teams, we need to be able to explain our work to several different audiences, and as such great communication skills are a must.

From left to right: Vivienne Ming, me, Debora Donato and panel moderator Sanghamitr­a Deb.

The second part of the discussion focused on how women can help shape data science. One challenge is getting more women into the field, which is closely related to encouraging women to pursue careers in tech in general. In my opinion, the industry needs to partner with universities and perhaps even secondary schools to help fix the so-called “leaky pipeline,” where the STEM (science, technology, engineering and math) fields lose more females than males at every rung of the educational ladder.

Another topic of discussion was what women currently in data science can do to help shape the general public’s image of data scientists. We should be present and vocal, attend meetups, write blog posts and do whatever else we can to share our knowledge and experiences.

The evening concluded with some questions from the audience. One man asked what he can do to create a welcoming and conducive environment for females as a male on a data science team. Vivienne gave a great answer: the predisposition to treat the minority differently in any environment can be subconscious, so one should engage in careful introspection to watch out for such inclinations.

It is always wonderful to get together with other women in tech and particularly in data science.  As someone who has spent so much time in male-dominated fields, I have gotten so used to having almost exclusively male colleagues that I rarely think about the causes and consequences of the lack of women in my space. This meetup pushed me to think about and discuss these issues for the first time in many years.

Shanshan Ding

Shanshan Ding is a Data Scientist I on the relevance team at Tagged.

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8 Takeaways from F8

I recently attended Facebook’s F8 Developer Conference. Here are my 8 takeaways:

1. Predictability

Facebook emphasizes getting a simple idea to production as fast as possible; the general sentiment is to build better quality code by default. To enable this, they focus on predictability throughout the code base. It should be easy for an engineer to read through the flow of the code. Simply put, given an input state, the output state should be predictable and reproducible. This philosophy has helped them maintain a manageable code base as they’ve scaled their engineering team. Predictable logic flows through the code, which allows them to spend their time gathering metrics and iterating as fast as possible rather than tracing through complex code interactions and trying to keep it all in their heads at the same time.

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Barrett Cook

Barrett Cook is an engineering manager on the web team at Tagged.

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Mobbing @ Tagged

Where it started

It’s 2 a.m. on a Friday. You have been sitting in a windowless computer lab in the basement of the CS department for almost the entire day. You and your three project partners are not out that night because every single one of you really loves writing low-level C code to optimize that matrix multiplication assignment due next week. You argue about implementation, make design decisions together, pass the keyboard back-and-forth – everyone’s eyes glued to one screen. You’re completely in the zone. You’re in sync. You have flow.

Achieving that flow is one of the hardest problems in the workplace. There are countless theories as to what is the best way to get there. But what if you just tried to do exactly what you did in college? That’s what we did at Tagged, and it worked.

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Albert Eloyan

Albert Eloyan is a Software Engineer I on the Tagged Web team.

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