The 5 stages of the data scientist - Technical.ly Philly

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May 15, 2019 10:34 am

The 5 stages of the data scientist

Freya Systems hosted a Philly Tech Week event to reconsider what we think we know about the ever-popular position.

Chris MacNeel displays popular Data Scientist descriptions.

(Photo courtesy of @genethorpephotography)

The role of the data scientist could be explained in a number of ways considering who you ask and on which day. The “look” of the data scientist is another point of contention — some opt for tip-of-nose glasses, others perhaps a man bun.

Such is the case for Chris MacNeel, the proud man bun-wearing senior data scientist for Freya Systems, the growing software development and data analytics firm based in Delaware County’s Media. Freya will celebrate 10 years of business this September after being founded by Ben Johnson, current co-owner and CEO.

Johnson, a Philly Tech Week fan and supporter of Technical.ly, decided that this would be the year that Freya would contribute to the great knowledge share that is PTW and host its first community-organized PTW event in the ‘burbs.

“There’s an itch to come together,” Johnson said of stretching PTW to Media and engaging the local tech community there. “While this was the first event organized by Freya, it won’t be the last.”

At the event, MacNeel presented “A Day in the Life of a Data Scientist,” alongside of presentations by Mary Kate Lo Conte and Marina Eyl of The Merz Group with the topic, “How Data Analytics Drive Brand Strategies and Success.” Johnson wrapped the event with a data visualization of publicly accessible information on the restaurants in downtown Media, sending guests off to dinner smarter via some useful data points.

So what is a data scientist? MacNeel simplifies the definition for us as: “someone who has the ability to take data and understand it, process it, extract value from it, visualize it, and communicate it.” He breaks a “day in the life” (perhaps more the “life of a project”) into five specific stages:

  1. Requirements
  2. Interpreting
  3. Cleaning
  4. Analyzing
  5. Storytelling

Data scientists come from all sorts of different backgrounds, but most critically come with a background in math of some sort. This is crucial for navigating systems, collecting data, interpreting and analyzing it. Something often not overly emphasized in a job description is just how much “cleaning” is required in the job. Forbes published survey results that show 60% of a data scientist’s time is spent cleaning and organizing data, which gets messy depending on the system it’s stored in, and who stored it.

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For Freya’s MacNeel, there’s an often overlooked bit of criteria for being a successful data scientist: having soft skills. Particularly during the requirement gathering stage and for the storytelling stage, the data scientist needs to listen, empathize and connect.

Event attendee Christa Ward of CJW Consulting shared this after the event:

“As data scientists, we have to remember the importance of storytelling,” she said. “As data collectors, we often are so involved with analyzing statistics, that we forget that sometimes the key stakeholders don’t care how the sausage is made. Data scientists have to have the ability to use the data to craft a good story for audiences that range from top-level executives to, as Chris put it, our most disinterested family member.”

Josh Stevens, a software engineer from Monetate, also attended.

“The data analytics made for an enjoyable evening,” he said. “Hearing from the various perspectives (that of a data scientist, marketers, and an executive) was very interesting and the candid discussion was insightful.”

We’ll be excited to see more tech community convening in Delco and throughout the ‘burbs. Until then, if you have a love for math and data with the soft skills to work with people and tell those final stories, maybe find yourself a data science position on our jobs board — and, oh, cool, looks like Freya is hiring too. Man bun not required.

Companies: Freya Systems
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