Kartik Mandaville co-founded SpringRole, a crowdsourced recruiting marketplace powered by referrals in 2014. SpringRole sets itself apart, going after the passive candidates through the network of its community. With a current network of over 8M passive candidates and an average 300,000 new users coming on board each month, SpringRole is poised to bring about a revolution in the recruitment space. Typically, a Job posted to SpringRole receives 100 referrals of which only 10% pass the initial screening phase, giving the employers the perfect candidate. Apart from his role at SpringRole, Kartik is also the Technical Advisor at Science Inc. in Santa Monica, California. Having graduated from Carnegie Mellon University with Masters from the Language Technologies Institute focusing on Big Data, Machine Learning, NLP and BioTech, he employs his expertise working with early stage startups associated with Science Inc, helping them out and mentoring their technology stack – database architecture etc. Kartik was in charge of the Science team that kick-started its India operations in Bangalore. The team today has over 25 software and product design engineers who work across the portfolio companies.
Kartik has a wide experience working with startups. Before joining CMU, he worked with Shareaholic as a developer working on the product distribution channel and other web properties. Many of you would recall AutoBudder– the app that automatically wished your friends on their birthdays; Kartik was the man behind it. Apart from that, he has also served as the CTO of Let Me Know, an online portal delivering internships, scholarships, conferences etc to college students in India.
Kartik did his under-graduation in Computer Science at MIT, Manipal. In an email interview with Kartik Mandaville, FWD Business tries to pick his brain to get more information about SpringRole and his other endeavors.
I was part of the team for IBM Watson in Carnegie Mellon University. Being part of the project showed that deep learning has great potential. I got my classmates together and set up a team of 7 to
build an engine which matches a candidate with a job in our final semester at Carnegie Mellon University. We built a product to get feedback from employers and this goes into the machine learning algorithm. On graduation, four of us decided to pursue and make it a real business. I pitched the idea to Mike Jones, CEO of Science (ex- CEO of MySpace) and because of our relationship it moved quickly. We came to Los Angeles and started building a business around our technology. From there, it was continuous iteration through customer feedback on business models and product. I was heavily involved in recruitment for startups and have personally hired over 45 people till date. So I combined both of them and came up with the idea of deep learning recommendation engine for figuring out if a candidate matches a job.
It is going to move towards temporary hiring. Companies would want to show a lean team and want to avoid overhead costs. Candidates want to learn fast moving jobs. In our times, job changes happen every 2-3 years which was unheard of in the previous generation. The trend is moving towards changing every 6 months. So the market will evolve to temporary hiring which is between freelancing and permanent. Today, there are 30 million independent workers in the US.
We are not just referrals. We are an endto- end recruiting platform. And yes an employer can always say no to a certain candidate but we avoid such situations by the rigorous screening process through the technology. Our success rate is 40%.
Yes, there should be and we are building it. We already have pieces of it – feedback loops, messaging and scheduling between employer and candidates.
There are thousands of companies in recruitment and some have tried to use technology. It’s a huge market and one of the few evergreen markets. LinkedIn recently announced that they are going
to use deep learning. We differentiate ourselves with our proprietary data and technology.
Yes, we built a ranking system based on the conversion and quality – we use it behind the hood to ensure quality.
Deep learning is more advanced than that. Like we would give different weightage to tier 1 vs tier 2, product companies vs service, startups vs enterprises, Masters vs Bachelors and so on.
In the last month, we released career pages and a simplified ATS. In the future, we plan to add more tools to our platforms like stack ranking, scheduling, comments and many more.
Yes, we are a startup and would love to work with startups. In fact, I would say a good number of our clients are startups.
Yes – we have a feature for candidates where they edit their profile to get a nice URL like springrole.com/kar2905 And employers – we are constantly improving the job pages. We just added
the company Video, tech stack, funding and facebook + twitter widget 4
Text: Philip Yeldhos Photos: Various Sources