Getting to Know Divyakumar Menghani

May 24, 2019

LinkedIn wouldn't be the company it is today without the engineers who built it and the talented individuals in technical roles across the company. They are the ones who create, build, and maintain our platform, tools, and features—as well as write posts for this blog. In this series, we feature some of the people and personalities that make LinkedIn great.

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Divyakumar Menghani is a Data Science Manager on the Hiring Marketplace Data Science team, where he works on Talent Solution products to help connect companies to talent, and people with jobs. Prior to joining LinkedIn, Divyakumar attended UC Berkeley’s School of Information, where he obtained a master’s degree in Information Management and Systems.

What is your role at LinkedIn and what does your team do?
Officially, my title is Data Science Manager and I lead a team of data scientists in the Hiring Marketplace Data Science team. However, my role and job truly is to help LinkedIn win! Our team leverages billions of data points in the Economic Graph and turns them into insights that improve the product and business model for Talent Solution products, such as Recruiter or Talent Insights. It is immensely satisfying to see the team’s work drive impact through connecting recruiters with top talent and helping seekers find dream jobs.

You started as an intern in 2014. What was that program like and what did you work on?
The 2014 class had three data science interns, and we all worked in the Mountain View campus. We’ve now grown to 18 interns globally for the upcoming 2019 class. The program was well-executed right from our first day in orientation to the last day, with many fun events. Throughout the interview process, I had the opportunity to talk to multiple team members to not only address their interview questions but also ask about and learn from their unique experiences at LinkedIn. We also had a fun trip to Napa and Disneyland with all of the other interns.

During the summer of 2014, I worked on quantifying a member’s professional brand on LinkedIn and determining what actions a member could take to improve it further. For example, how might a job seeker improve their profile to increase the odds of getting hired, or how might a new member find connections or groups to improve their network?

When I started, I was fairly nervous about being able to fit in alongside PhDs and team members with 8-10 years of data science experience. But to my surprise and relief, I realized in my first week that the people around me were not only the smartest but also the humblest team members, who cared about my growth. I had a lot of autonomy on the direction I wanted the project to follow and learned new technical skills in the short span of 10-12 weeks. The people I met that summer helped me navigate through the early part of my career and continue to be my mentors even five years later.

After your internship, you started working as a data scientist, and now you are a data science manager. What has it been like going through that transition?
Transformation is at the core of LinkedIn’s culture and I am fortunate to have had a few transformative experiences myself. In 2014, I was a summer intern and had the opportunity to continue working part-time until December 2014. I came back full-time in June 2015 as a senior data scientist on the Recruiter product, focusing on InMail ecosystem. In October 2016, I was promoted to staff data scientist. It was also around this time that I expressed my long-term career interests to enter into a people management role. My managers (Vibhu Saxena, Cindy Zhou, Kuo-Ning Huang) and mentors (Archana Sekhar, Shalini Agarwal, Chi-Yi Kuan) were very supportive throughout every step of this journey with me during the Apprentice Manager Program (AMP), a 10-week period where I was an acting manager for two direct reports. In retrospect, I learned a lot during my transition days. Within a few days of AMP, I was in the middle of challenging debates on metrics, project/resourcing priorities, long-term planning, and hiring. I also learned how to help team members grow professionally and create opportunities matching their passion and interests. All these instances taught me a lot about myself and others, as well as rapidly evolving my views on management in the context of data science. Over time, I have had the privilege of hiring and mentoring a team of 8-10 data scientists; I still learn something new about management and myself every day.

What are some of the coolest projects that you and your team have been working on right now?
One of the projects I am most proud of is Diversity Insights. It is a huge cross-functional effort to bring this capability to our customers. My team drives the insights and strategy on how might we build and embed diversity by design into our hiring products. An example is Representative Ranker, where we experimented with various options to see how we can improve the representation of gender in Recruiter search recommendations. It is incredibly rare to have an opportunity to work on such interesting and complex problem spaces, while also being surrounded by team members you enjoy working with.

How would you describe the engineering culture at LinkedIn?
Broadly, the culture at LinkedIn is very collaborative and fun. Most of what I love about the company involves the people I get to work with. As data scientists, we tend to work with cross-functional teams, yet there is a strong sense of “one team,” which is driven by the time we spend together to view and solve a problem from multi-disciplinary lenses. In a typical week, I get to collaborate with application engineers, data engineers, product managers, marketers, sales reps, customer success reps, and operations. I also get to work closely with the leadership in different teams to share what the data is suggesting and make recommendations impacting our products. It is incredibly fulfilling to see how partners and leaders value data science to make strategic investment decisions.

I also have the privilege of being a Culture Champion here and contribute in organizing InDay events. Each month, LinkedIn gives its employees a day to invest in themselves and their communities. For example, our May InDay theme was around giving back. These days embody our values of team building and giving back. I have enjoyed leading and volunteering at InDay events to spread the unique culture we have here.

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For our Relationships InDay last September, we hosted a Puppy Party!
 

What are your favorite things to do when you’re not at the office?
I enjoy reading a lot—non-fiction slightly more than fiction. I own 300 or so hardcover and paperback books, and about 6,000 digital books. My all-time favorite books are the Incerto series by Nassim Taleb, Option B by Sheryl Sandberg, and any book by Ryan Holiday.

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