Chuck Utterback, a June 2021 Data Science graduate from Flatiron School, came to his program with decades of professional experience.
He shares why he chose to attend Flatiron School to upskill in data analytics below.
Background in Business
Chuck Utterback began his 30-year career with an MBA in finance. While he initially followed the traditional path by working as a Financial Analyst, he soon transitioned toward data.
“I derive intense satisfaction in developing business insights through data engineering and analytics. Today’s technology, such as cloud computing, advanced data visualization tools, and analytics programming languages, enable iterative and rapid time to insight.”
In the subsequent years, he held a string of data-focused leadership roles in prominent companies and founded his own analytic consulting company.
“Within years of starting my career, I migrated into cross-functional business analytics. [But] to answer complex business questions, I found the data sources insufficient,” he said. “To remedy this, I began building data warehouses, leading to 15 years of consulting projects in data warehousing, data visualization, and process improvement.”
Bootcamp Experience
After 15 years, however, technology had changed. To keep up with evolving capabilities, Chuck determined it was time to go back to school and update his skillset.
“I decided to pause client work and invest in developing more profound data science and machine learning skills,” he said. “I aimed to bring more robust statistics and machine learning techniques into my existing analytics practice. ”
Choosing Flatiron School, Chuck said, was the result of an analysis combining several factors and features of its programs.
“Flatiron [School] had the best combination of course materials, commitment length, and remote flexibility. I chose the full-time data science bootcamp and focused all my energy there for six months.”
Even before the program began, Chuck’s skillset quickly began to expand.
“The onboarding assignment was to use Python to code gradient descent calculus equations,” he explained. “The project stretched me from the start but was foundational to getting comfortable with Python functions.”
The coursework, he said, had relevancy to his practice throughout the program.
“I liked learning classification models due to their relevance to solving business problems like customer segmentation/churn and predicting various outcomes across any business process.”
Working With Data
Unlike most Flatiron School students, after graduating in June 2021, Chuck returned to where he began – using data to reduce his customer’s friction, find revenue opportunities, and expose process inefficiencies. The transition back into using data to meet clients’ needs – as opposed to creating projects for a grade – has been a fluid one.
“I love [what I do]. I target to keep at least 80% of my time heads-down (versus meetings), solving problems using data.”
As for his new skills, he’s already putting them into practice.
“I use Python to extract customer data from Salesforce into Google Big Query and automate data quality applications and customer insights. Overcoming poor data quality is a considerable impediment to advanced techniques.”
Reflecting On His Journey
Looking back on his time at Flatiron School, Chuck’s main takeaway is to always bet on oneself, and never stop learning.
“Embracing continuous learning by investing in myself – upskilling within analytics through Flatiron – drives a positive return on investment.”
His advice for other data science students is to remember that Flatiron School is just one piece of the puzzle, it’s critical to prioritize being a well-rounded applicant.
“Formalize daily habits in data science coding and reading that go beyond the Flatiron curriculum so you can sustain momentum after graduating.”
Connect with Chuck on Medium or LinkedIn.
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Read more stories about successful career changes on the Flatiron School blog.
