At Cherre, senior hires are often asked the question: “What can you do better than anyone else in the world?”
“What an arrogant thing to answer, right?” said CEO and Co-Founder L.D. Salmanson.
Maybe for companies looking to hire generalists, but for Cherre, a real estate data platform, Salmanson said they want experts.
“We want people to have enough ego to say they’re the best in the world and, at the same time, be able to say they’re open to learning and growing from other people on the team,” Salmanson said.
Like CTO Ron Bekkerman, who joined Cherre at the end of 2018. The list of accolades he brings to the table includes, but are not limited to: a Ph.D. in machine learning, a data science professor role at the University of Haifa in Israel, a founding role on LinkedIn’s data science team, and research and engineering positions at Google, HP and Motorola.
That’s not to say Bekkerman isn’t on the front lines: He’s often chatting up employees around the office and seeking new hires who will help the company during its new stage of growth.
Salmanson said this blend of humility and self-recognized excellence, two of Cherre’s core values, helps build trust across the 50-person organization, which shapes Cherre’s cross-disciplinary environment filled with experts from engineering, data science and more.
A “true meritocracy”
Recruiting experts, or “snow leopards” as Cherre calls them, can take time.
Before making any decisions around hiring, technology and strategy, the team presents a thesis on the proposal and the reasoning behind it.
“We do a lot of writing and PowerPoints here,” Salmanson said. “Every decision comes with a thesis. Then we revisit it afterward to see if that decision made sense.”
Although time-consuming, Salmanson said this process keeps everyone on the same page and in check while providing an opportunity to adjust future decisions based on the results. It also allows time to ensure the best ideas rise to the top, forming what Salmanson calls a “true meritocracy.”
MEET THE SNOW LEOPARDS
“We surround ourselves with inquisitive, smart people who are better at everything we do because we know we suck at a lot of things,” Salmanson said. “We hire to fill in those blanks and listen to ideas from all levels.”
This includes suggestions from Cherre’s group of junior developers, who Salmanson describes as holding “extremely dangerous positions from a management standpoint.”
“Junior developers here have a lot of autonomy and control,” Salmonson said. “The vast majority of our technology decisions come from the very bottom.”
Built without blame
Cherre’s VP of Engineering Stefan Thorpe ranks trust as the most important element of his team and has put several initiatives in place to bolster it. He says trust begins with the formations of teams.
Engineers are split amongst five smaller teams typically consisting of five to six people and act as specialists alongside a full complement of experts from other departments. Led by a product manager, groups often include data engineers, machine learning engineers, data scientists and full web stack engineers.
“All of our teams are cross-functional, which allows each one the autonomy to carry out end-to-end what they need to work on,” Thorpe said.
Cross guilds of people in the same roles, like data engineers, then meet on a weekly or bi-weekly basis to share what they’ve been working on and what tools they’ve been using.
“This naturally forms several levels of collaboration in preparation for a major release where we’ve got all five teams pushing products toward it,” Thorpe said.
Skill Self Assessments
Thorpe also has in play a blameless postmortem methodology, which, when something internal goes awry, ensures there are no pointing fingers.
If Cherre’s GitHub page goes down, or its continuous integrations slow, team members associated with the project are pulled in to identify the error and come up with a fix.
Once the issue has been addressed, those involved meet for a blameless postmortem. This directs attention away from individuals who may have submitted code incorrectly and shifts it on prioritizing system changes to avoid errors in the future.
“If you end up blaming one another, you end up in a culture that gets stuck on issuing fault, which immediately degrades trust,” Thorpe said. “If everything is systems-related, you take the human element out of it and the finger-pointing.”
Data science, front and center
Data science is the culture at Cherre. According to Bekkerman, there’s no separating the data science team from the larger company.
“We are an AI company and there is a data science aspect tied to every activity here,” Bekkerman said.
Bekkerman first observed this daily integration of data science across an organization during his time at LinkedIn as a senior research scientist. He liked it so much that he brought the practice to Cherre.
For example, if the team is building a dashboard to present data to customers, a data scientist reviews it to ensure the data is correct. Or, if at a business meeting a prospective customer requests a custom add to Cherre’s platform, a data scientist immediately assesses whether it’s doable or science fiction in the meeting.
“Data science is much larger than just one function that deals with one problem,” Bekkerman said. “We are an integral part of Cherre’s day to day.”
For that reason, Bekkerman asks his growing team of data scientists to seek out and speak to teammates from every department once they join Cherre.
“Even if they don’t want to, I kind of insist,” Bekkerman said. “Data science is everywhere here, so it’s important that we’re everywhere.”