Schinria Islam Uses Data Science for Social Science Insights at Uber

Schinria Islam has a curious job title: Senior People Research Analyst at Uber. It’s her job to couple data science with social science to study “the employee experience at Uber.” She’s part of Uber’s People Analytics team that provides data and research about the company’s global workforce. 

“As a quantitative and qualitative people researcher,” she adds, “I’m passionate about deriving data-driven insights to shed light on human behavior and help organizations maximize their future impact.”
 
Having graduated from Columbia just two years ago with a master’s degree in Quantitative Methods in Social Sciences, Islam is already making an impact. At Uber her work analyzing and synthesizing employees’ ideas was the underpinning for Uber’s new cultural norms. And she and her team traveled internationally to host design-thinking workshops that inspired the redesign of Uber’s performance management system. She and her team also led a mixed-method research project to identify the core competencies of effective managers at Uber, research she presented at the Society for Industrial and Organizational Psychology Conference in April in Chicago. Much of her recent research has focused on diversity and inclusion, an area Islam says “is of high priority to me personally and of high priority to Uber’s leaders.”
 
In the fall of 2018, she’s returning to academia to begin a doctoral program at UC Berkeley, where she hopes to “explore what lies at the intersection of data science, psychology, and technology” and “to assess the impact of that space on society.” In this interview, she discusses her job, her plans for graduate school, and her deep and abiding interest in using data science for good.  
 

 

Can you talk about your job at Uber?

It might be surprising to learn that Uber is only eight years old, which means that we still have a scrappy environment that enables us to think big and move quickly. The agility I have as an employee–in alignment with the fact that Uber is one of the fastest-growing technology companies in the world–enables me to conduct research that is timely and impactful. As a company, we’ve experienced immense cultural change. To navigate those changes in a thoughtful way, the People Analytics team provides data and research insights regarding Uber’s global workforce.
 

What is the most interesting aspect of your job?

The most interesting aspect is being able to leverage employees' feedback in my research to make recommendations to leadership about suggested changes for the company. Hearing directly from Uber’s workforce – through quantitative and qualitative research – enables us to take action on the voices of thousands of employees globally.
 

Your master’s degree was Quantitative Methods in the Social Science (QMSS) with a focus on data science, a program within the Graduate School of Arts and Sciences. Can you discuss that program?

Schinria Islam, Data Science Student
QMSS is an intensive, interdisciplinary degree that emphasizes the learning and application of quantitative research methods from various disciplines, including economics, statistics, psychology, computer science, and sociology. I pursued the data science focus of the program and completed courses such as applied data science, quantitative theory, data mining, social network analysis, data  visualization, data analysis for the social sciences, and regression modeling of temporal processes. 
 
Much of what I do in my current role is an application of my learnings from Columbia, so QMSS was a good choice for me. My background is in economics, psychology, and applied statistics, and I found QMSS to be fitting for my multidisciplinary background and interests. Shout out to Dr. Gregory Eirich from QMSS and Dr. Tian Zheng from the Statistics Department and the Data Science Institute. Their classes taught me the most, and their research and leadership most inspired me to pursue a Ph.D.
 

Why did you decide to return to university?

Shifting a company’s culture through data and research has been a challenging and inspiring experience for me. At Uber, I’ve been empowered by my managers to support and drive research initiatives, to develop and test my own hypotheses, and to engage with leaders across the company. I’ve been able to work on projects that impact thousands of employees, and as a result, millions of driver partners and riders globally. I am naturally a curious person, but it wasn’t until I came to work for Uber that I felt I could really voice my ideas, ask tough questions, and drive research that explores those ideas and investigates those questions. More than anything, my current role made me fall in love with doing research. I’ve seen how valuable research has been in guiding critical business decisions within the ever-evolving environment of a global tech company. Beyond recognizing its importance, I’ve found that doing research is pretty fun, so pursuing it as a career long-term is probably a good call for me.
 

What motivated your decision to pursue a Ph.D.?  

Columbia’s data science curriculum exposed me to a wide range of analytical techniques. I’ve applied those learnings in my capacity as an analyst and, along the way, have realized some areas that I’d like to explore further. Thus, my experiences at Columbia and Uber were the impetus for my desire to study the data and information field more deeply – in both a practical and philosophical sense.
 

How did you choose your doctoral program? 

What ultimately sold me on the program was the opportunity to work under the direction of Coye Cheshire, whose research on social exchange, trust, online behavior, and technology-mediated social participation using mixed-methods and multidisciplinary approaches strongly aligns with my ambitions. I feel really lucky to have been selected for the opportunity to be advised by Coye and to learn from reputable faculty. I am very excited (a bit terrified, but still very excited) to start this next chapter of my life as a Ph.D. student. I am hopeful that my experiences will enable me to grow into a more impactful and mindful researcher, data practitioner, and leader. 
 

How did you develop your interest in applying data-science to solve sociological problems?

I am a first-generation Bengali-American and my parents immigrated to the United States about 30 years ago. I was lucky to be born in the U.S., but exposure to poverty and inequality while visiting Bangladesh at a young age played a huge role in my development and in shaping my interests. So even as I’ve explored different roles in research and analytics, I’ve always been primarily guided by my desire to understand and improve the human condition.
 

What are your thoughts on the responsible use of data? 

My background is in data science, and I am very much a data enthusiast. However, being a data practitioner within a people-oriented field has taught me that data is powerful and that, with that power, comes great responsibility. I have also come to realize, on a broader level, that data isn’t everything. I’ve found that meaningful insights can be extracted from large data, but they often only tell part of the story. I believe data should be paired with human judgment and oversight in order to ensure fair outcomes for people, and without proper guidelines or parameters, data can easily be misinterpreted, misused, or taken out of context.
 
Data science methods and technologies that aggregate information enable companies and individuals to quickly and scalably extract insights and anomalies. Without special attention, however, I believe that algorithms can reinforce negative stereotypes or inadvertently learn bias from the people who build them - and we are all unconsciously biased. For me, the rate of innovation in the technology and data science communities, and the increasing reliance companies and individuals have on what is created, only magnifies these risks. It underscores the need and urgency for scholars and practitioners to understand and shed light on these grey areas. Thus as a Ph.D. student I hope to explore the design, ethics and usage of data, information and technology, and I’d like to assess the impact that these elements have on individuals and society.
 
—By Robert Florida


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