Have you ever had an idea that you just couldn’t get out of your head? A dream that, no matter how hard you tried to ignore it, just kept popping up. If so, honor that inclination. As today’s guest says, if you can’t stop thinking about it, you should probably go for it. 

In this episode, I’m chatting with Jack Mengel about his leap from project management to data science. Jack is sharing how he went from merely dreaming about a career in data science to being “all in” for his leap in just a matter of weeks. Plus, he’s shedding light on some of the limiting beliefs he encountered along the way and how he overcame them.

In this episode, you’ll learn...

• Where Jack started his career and where he is now [1:52]
• How Jack accidentally landed in a project management role [3:42]
• How turning 30 inspired Jack to make a change in his career [7:55]
• Why Jack was drawn to data science, and why he was initially hesitant to go for it [10:45]
• How Jack went from not knowing what he wanted to do to being all in for his new career in just a few weeks [18:06]
• Why Jack decided to work with a career coach before he took his leap [19:26]
• How Jack taught himself the skills he’d need for his new career [23:33]
• How your identify shifts and evolves during your career leap [28:03]
• How Jack landed a data science role at his original company [30:30]
• Using your passion to fuel your leap and make the hard work enjoyable [36:02]
• Putting yourself out there to make connections and land projects in your new field [37:20]
• How to overcome the limiting beliefs keeping you from taking your leap [44:30]

If you’re waiting for a sign to take your career leap, be sure to tune into this episode.

Get full show notes and the episode transcript: https://www.lisahoashi.com/leaplikeme/episode25

Connect with Jack

Jack’s Instagram 

Jack’s Bio:

Jack Mengel is an experienced Program Manager and Data Science Engineer, based in Boston. He graduated from Boston University in May 2021 with a Masters in Computer Science (concentration Data Analytics).

In his current role, he is a full-time data scientist. He has performed projects predicting returns of stocks as well as trade costs, using both classifier and regression approaches. He has constructed a series of models using gradient boosting to predict trade costs for globally traded stocks that is now used in his prior company's trading process.

His data science work has also been heavily involved in "natural language processing" (aka NLP) meaning he derived statistical insights using text. His work in this space has been primarily looking for sentiment / investment signals on companies in earnings calls and company filings.

Jack has competed in several Kaggle competitions. Here is a link to his notebooks: https://www.kaggle.com/jacksmengel/notebooks