Dear Analyst #94: Helen Mary Barrameda on having a “portfolio career” prior to being a data analyst, winning the NASA Space Apps challenge, and wfh tips

A common theme I’ve noticed from talking with many data analysts and data engineers is that they didn’t come from a “data” background. Helen Mary Barrameda someone who exemplifies this theme. She is based in the Philippines and started her career as a freelance writer in 2004 writing lifestyle pieces. She used her earnings from her writing gigs to pay for her engineering education, and eventually became a geodata engineer working in the field of Geographic Information Systems (GIS). In this episode, she discusses falling in love with Python, how her engineering background helps with a career in data, working from home before everyone did it, winning the a NASA challenge, and more.

How web development can help with your data analyst skills

Helen started her career in geomatics. Prior to this conversation I didn’t know much about this industry:

Geomatics is the integrated approach of measurement, analysis, and management of the descriptions and locations of geospatial data.
Source: University of Florida

Over time, Helen realized there wasn’t a lot of creativity in the geomatics space. Most of her time was spent doing research and publishing for scientific journals. It was time for a change.

Due to personal reasons, she decided to look for jobs and projects she could do entirely at home before the working from home trend really started. Given the engineering background, she started picking up projects in web development marketing automation, data analysis. She realized she could be a lot more creative with these web development and data jobs versus her old career in geomatics.

Falling into data engineering

As Helen continued taking on projects while working from home, data became more prominent in her projects. She worked with an ad tech company where she helped with getting data from their website into their CRM. She was doing a lot of data cleaning and was actually doing ETL (Extract Transform Load) for her clients. Before she knew it, she was doing data engineering work.

Helen decided to find some data science workshops in the Philippines and started working on a Master’s degree in data science. While her geodata engineering experience helped with some of the coding skills required in her data science projects, she felt that learning algorithms was still difficult.

Like many people I’ve spoken with on this podcast, people fall into data analysis and data engineering. You work on data projects without realizing you are actually doing things that a data scientist is doing. And if you want to formalize the skills you are acquiring, you can go back to school like Helen did. In Helen’s words:

I learned the practical application of data skills before learning the theory.

Building a “portfolio career”

As Helen discussed her various roles and projects, she brought up a phrase I haven’t heard before when you are progressing through your career: the “portfolio career.”

In HR speak, I think this is analogous to people who call themselves “generalists.” Helen has gotten exposure to a variety of industries and people. She brought up an interesting point about how most data analysts progress through their careers. They are laser focused on their field or industry, and maybe don’t have the time, need, or desire to interact with the C-suite, for instance. Helen talked about the benefits of working with all types of people in your organization to help move your projects along; especially if politics or bureaucracy is slowing your project down.

I’ve spoken before on the benefits of being a generalist in your career. Take listen to this old episode from 2019 where I discuss David Epstein’s book Range: Why Generalists Triumph In A Specialized World. Cliff notes from the book via Four Minute Books:

To become excellent, don’t specialize early in life, experiment with many different paths.
You will be better at innovating and more successful if you have a breadth of experience.
The more famous you become for being an expert in one area, the more likely it is that you will be terrible at making accurate predictions about your field.

The traditional thinking behind being a specialist is that you can become the only person that understands how X works and therefore you maximize your “rate” for being an expert. I don’t think there’s a right answer, but personally I’ve found decent success from being a generalist.

Pregnancy, weightlifting, and Excel

The conversation took an interesting turn as Helen started talking about her pregnancy. While she was pregnant, Helen collected a ton of data about her health and vitals. Most of the data she collected was from analog devices like a blood pressure reader. With all these data points, she eventually created some descriptive statistics that she could share with her doctor during her pregnancy. Imagine being the doctor who gets to analyze data that’s already well organized and formatted!

Helen’s interest in tracking her health carried over into her weightlifting passion. She got addicted to weightlifting during the pandemic and started tracking the calories she was burning in Excel. This eventually led her into the field of biohacking.

Most of the data she was tracking came from her Apple Watch. She found a way to export the data from her Apple Watch into a CSV and could analyze her data in Excel or some other tool once the raw data became available.

Winning the 2020 NASA Space Apps Challenge

During the pandemic, Helen was working for a company called Cirrolytix and the company sponsored a team for the 2020 NASA Space Apps challenge. At the time, Helen was doing her Master’s degree in data science. Helen eventually joined a team along with some other data science students from her program.

NASA’s Space Apps challenge focused solving challenges brought on by the pandemic. The hackathon was done virtually for the firs time. Out of 2,000 teams that entered, Helen’s team was one of the 6 finalists selected. Helen’s project was called G.I.D.E.O.N. (Global Impact Detection from Emitted Light, Onset of Covid-19, and Nitrogen Dioxide). Here’s a summary of the project from their website:

GIDEON is an integrated public policy information portal that aims to measure the impact of COVID on various countries and its effect on economic and environmental terms. The countries that are able to contain COVID while keeping their economy afloat with minimal impact to the environment stand the best chance of sustainably bouncing back after this crisis.

The result was a traffic light system for whether a country could open back up given the current spread of COVID. Here’s an example of the country-level dashboard the tool could create using Helen’s home country:

Even though the hackathon was only 2 days, Helen’s team was able to tie a bunch of datasets together to help create this traffic light system. It’s interesting how the team used emitted light and nitrogen dioxide levels obtained from satellite imagery to look for trends. Take a look at their methodology and insights on their project website.

How to be productive while working at home

As the episode wrapped up, Helen gave some tips on how to be productive while working from home. At the end of the day, she said it’s all about energy management instead of time management. A few things she does to manage her energy:

Aesthetics of your work station impacts how productive you are
She breaks up the day with menial tasks like creating a grocery list
Meditation and breathing work

She mentioned an app called Focusmate that matches you with strangers who also want to be more productive and get work done. Accountability is the name of the game here and that’s how Focusmate has helped Helen when she’s really feeling a lack of productivity.