Welcome to our monthly series, “Why I joined Asana”! Every month, we talk to Asanas across our teams and offices—from Dublin to Sydney—to get to know the people inside the company and learn why they chose to work here.
Rishika Dhody is a Data Scientist in our San Francisco office. As part of the data team, she works closely with our product, customer success, and sales teams and is instrumental in architecting and building our data infrastructure.
At Asana, we rely on data to inform us on the impact we’re having on our customers. By understanding our company’s goals and proactively informing a direction with data, our product can help more teams do great things. Read more about Rishika and her journey to joining #teamasana.
I initially became interested in Asana because it sparked my academic curiosity as a company dedicated to helping people work together effortlessly. During the interview process, I spoke to a lot of unassuming, considerate, and enthusiastic Asanas. I found that this group of people were all working together towards achieving a common and clear goal. This met my personal needs, which was to experience growth amongst a motivated team, and immediately piqued my interest in working at Asana.
As a data scientist on the data team, I partner with the product teams and help them gather, query, and interpret data to address customer needs and explore possible solutions. This involves working closely with user experience researchers, product managers, and engineers.
The synergy between these three roles is one of the more interesting aspects of my role. Most decisions are born from a mix of a vision, some intuition, some data insight, and resource limits. Understanding and contributing to optimizing this synergy between teams is an ongoing process, which helps me grow both as a data scientist and as an effective teammate.
At Asana every data scientist gets the opportunity to work with different teams. At the beginning of every sprint we go through the top goals, priorities, and accomplishments of each data scientist. This exercise is so motivating because it exposes the various approaches and questions that data can help with.
I also get excited about the diversity of opportunities available to me as a data scientist at Asana, allowing me to move towards my personal goal of understanding bias and motivation, while contributing to achieving the larger company mission. With every data scientist working with a different team, and bringing their unique perspectives and skill sets to the table, there are so many avenues from which this complex topic can be explored.