Episode 64 - Pro Tips for Your Resume with Marc Cenedella
Marc Cenedella is the CEO of Ladders, Inc, and today he talks to Max about the Ladders Job Search service, and the job matching problem in the 21st century. After diving into The Ladders’ specific audience and product approach, the conversation turns to Max’s resume. The advice provided is invaluable to all job seekers - present and future - out there.
Links from the Episode
The single biggest mistake you are making with your resume
The Ladders 2019 Resume Guide on Amazon
The Ladders 2019 Interview Guide on Amazon
More about the Ladders 2019 Resume Guide
About Mark Cenedella
Marc Cenedella is the Founder and CEO of Ladders, Inc., a leading professional careers site. He is the author of the largest career advice newsletter in the United States, reaching an audience of nearly 10 million weekly.
A nationally renowned thought leader on job search, career management and recruiting, Marc is frequently sought out by national media organizations for his expert commentary on employment and entrepreneurialism. He has been profiled in The New York Times, Wall Street Journal, Fortune, Wired, and Businessweek, appeared on CNN, Fox News, MSNBC, CNBC, and Bloomberg and has spoken at Ignition, SHRM, and Internet Summit as well as Harvard Business School, Columbia University, and Yale.
Marc is also the Founder and Organizer of iOSoho, New York City’s largest iOS Engineer Meetup, as well as a mentor at TechStars. Before founding Ladders, Marc was a Senior Vice President at HotJobs.com, where he served as lead on its sale to Yahoo in 2002 for $436 million.
Marc on theladders.com
Marc on Twitter
Related Episodes
Episode 63 with Bethany Chrystal on strategies to manage your career
Episode 60 with Hilary Mason on Data Science Jobs and Descriptions
Episode 57 with my analysis of Data Science Job Titles
Episode 55 with David Auerbach who wrote about his experience with taxonomies and classifications which is an issue that Marc’s team has worked through with job descriptions at Ladders.
Episode 35 with Camille Fournier on Engineering Management Careers
Max’s Resumes and New Bullet Points
One of the most fun parts of this show was having Marc Cenedella look over my resumes. The feedback was live - I had no idea what he was going to say. I will post the two resumes here, my most recent resume (since before I started at Luminary in February 2019) and also my old resume from 2007. Then, I will list a few bullet points I could have added to my new resume in the style Marc had recommended in the interview:
My 2018 Resume/CV that I submitted to Marc
My old 2007 resume
Here are some potential new points, including a success verb and a number. This is still a work in progress (sort of a workshop result of my discussion with Marc) and so some more iterations will still be needed. I think I still need to make some of them shorter, and also take into account another point Marc made which is to think about your next employer. Some of these would change in words depending on who I would be talking to:
Designed and developed Foursquare’s Machine Learning methodology for Ad Attribution, increasing the number of statistically significant reports by about 30%, and increasing the number of controlled variables in the attribution reports from 5 to hundreds.
Consulted with the Foursquare Sales team on the pain points for attribution clients - mostly large national chains and brands - and built several features that allowed more reports to go forward contributing directly to the 100% year-over-year growth in revenue sales for that product.
Collaborated directly with the Foursquare Founder to design and launch Marsbot, a new product that reorganizes 6 years of work into a brand new place recommendation system with a natural language interface for the purpose of demonstrating Foursquare’s innovative ability. The app received critical acclaim from industry watchers, including Mashable’s 12 best iPhone apps of 2016.
Built the algorithm and data pipeline for Foursquare Venue Ratings, scaling it to calculate ratings for tens of millions of Foursquare venues, and calculated sentiment on tens of millions of Foursquare tips in dozens of different languages.
