A Data Science Evangelist Career Path
Careers flow from a personal mission, not job titles. But while the advice “do what you love” is sound, it’s also unhelpful. Does anyone love machine learning? Or do they love solving mysteries with it? Moreover, according to Cassie Kozyrkov’s data science roles that matter, there are at least 11 essential data science roles. That means there are 39 million possible data science career paths to follow!
As the Cheshire Cat warned Alice, if you don’t know where you’re going, any path will take you there. So I analyzed my favorite data scientists. I loaded my data into Spotfire... looked for patterns…
Five paths emerged. Think of them as driving routes you might get from Waze. Each has multiple turns. Each is motivated by a passion, or destination. The first is the passion to persuade. I call it The Evangelist.
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Catalina Herrera is one of my favorite data science evangelists. Last week, she shared her story with Kate Strachnyi on DATAcated. Her first job was as an engineering professor in her home country, Colombia. As a teacher, she discovered a passion to “connect the dots” for people. That design motivates evangelists. Her career spans 20 years and touches on all 11 roles in Cassie’s rubric:
YEAR ONE: Catalina ditched her teaching job, moved to the United States, and took a job with Texas Instruments. Her first mission was “to optimize the 10,000 steps required to make a chip.” Her foundation of teaching and engineering gave her good scores on analytics (role #2), data (#0), and social science (#10).
YEAR FIVE: After five years at TI, her data (#0) and analyst (#2) skills took off. Explaining her findings developed storytelling (#10) and leadership (#1) skills.
YEAR TEN: Catalina branched out as a consultant (social science, #10) and learned new business domains (specialist skills, #9: finance, manufacturing, and energy). Simultaneously, she deepened her skills across the data science technical spectrum (research, management, ML, etc.: #3, #4, #5, #6, #7, and #8).
YEAR TWENTY: Today, Catalina guides our internal community of practice. She’s a mentor. She leads industry-wide consortiums in the energy sector. She evangelizes all things data science.
Catalina exemplifies the distribution of skills for a data science evangelist. This Spider Chart below shows her career development. Each “hand on the clock” is one of Cassie’s 11 data science roles, in order of priority, beginning at 12:00 with Data and Leadership:
Evangelists have advanced skills to lead, persuade and communicate. They also have a strong and diverse data science background. They’re good team players.
Evangelists are rebels with a cause. I write about them a lot here, from GOATs like Florence Nightingale, Joseph Minard, and W.E.B. Du Bois to modern masters like LinkedIn’s top voices of AI and data science. Enjoy listening to Catalina’s journey with Kate Strachnyi and her passion for helping people connect the dots.
Post Script:
I was surprised by the interest in this topic. Last week’s posts on The Data Science Halo Bias Effect, and Visualizing Cassie Kozyrkov’s 11 Data Science roles generated over 80,000 views on LinkedIn and lots of interesting comments that helped shape this post—thank you!
Stay tuned for data paths 2-5, coming soon.
