Ling Shen, Chad Pickering, and Jing Huang

Photo Courtesy of Hai Yang
From left: Cristina Tortora, Chito Hernandez, Bhramar Mukherjee, Bin Yu, and Rajesh Parekh at the SFASA chapter’s gathering in January

Photo Courtesy of Hai Yang
SFAS panelists and SFAS officers, from left: Ron Yu, Charles Qi, Ray Lin, Li Zhang, Jing Du, Rajesh Parekh, Cristina Tortora, Bin Yu, Alexandra Piryatinska, Bhramar Mukherjee, Tao He, Chito Hernandez, Jing Huang, Ling Shen, Ruixiao Lu, and Kathy Zhang

Nearly 100 ASA San Francisco Bay Area Chapter (SFASA) members gathered at San José State University January 26 to celebrate the arrival of 2020 with an event that included keynote presentations, a panel discussion, sponsor presentations, dinner, and social networking opportunities.

Keynote Presentations

Four invited keynote speakers shared their views during 30-minute presentations. Bhramar Mukherjee, John D Kalbfleisch Collegiate Professor and chair of biostatistics in the school of public health at the University of Michigan focused on the nature of data science and its three key elements: statistics; computer science; and domain knowledge. She touched on the meaning of data science beyond algorithmic prediction and cited Miguel-Herman, saying “A hallmark of intelligence is the ability to predict counterfactually how the world would change under different actions by integrating expert knowledge and mapping algorithm.”

Chito Hernandez, group vice president at BioMarin Pharmaceutical Inc., shared his perspective on the career of data scientists in the era of big data. He emphasized that passion with purpose is the key to a successful career and a meaningful life. He shared his personal journey, as well as his daughters’ stories, to highlight the importance of passion. He also recommended everyone think deeply about their passion and purpose. He said passion alone is guaranteed to fall short.

Bin Yu, chancellor’s distinguished professor and class of 1936 second chair in the departments of statistics and EECS at the University of California, Berkeley, proposed the predictability, computability, and stability (PCS) framework for veridical data science, including PCS documentation that records human judgment calls in the data science life cycle. She also proposed the PDR desiderata for interpretable machine learning as part of veridical data science (with PDR standing for predictive accuracy and relevancy to a human audience and a particular domain problem).

Rajesh Parekh, engineering director at Google LLC, explained that Google has deployed cameras all over the world to gather street views. These imaging data and crowdsourcing were fed into artificial intelligence to enable business recognition and capture changes in our environment.

Panel Discussion

Cristina Tortora, assistant professor in the department of mathematics and statistics at San José State University, moderated as Mukherjee, Yu, Hernandez, and Parekh provided responses to the following questions:

What are the codes of ethics? How does one deal with pressures in publication

Yu cautioned about being compelled to publish because of a significant p-value. While the p-value remains a useful statistic in hypothesis testing, we as statisticians must acknowledge limitations of the study and work closely with domain-specific scientists to understand scientific implications.

Mukherjee elaborated that statistics is not just about crunching numbers such as p-values; the focus, rather, is far more fundamental—serving the scientific community and general public.

Hernandez responded with a thought-provoking analogy: You should only feel comfortable publishing if it could withstand the scrutiny that would follow if it were reported on the front page of The New York Times.

What are statistics job prospects in terms of compensations in different industries?

According to Yu, the top job markets for UC Berkeley statistics students are high-tech companies, fintech companies, academia, biotech companies, and entrepreneurship.

Hernandez noted that today’s students are drawn to high-tech companies. They offer incredibly high salaries. A data scientist can have an annual salary as high as $200,000 with just two years of experience.

Parekh said the high salaries at Google can be justified by the impact of the work itself.

Yu said today’s students are more socially conscious compared to previous generations and, as a result, inspired to contribute to society. The social impact of high-tech companies such as Google, Facebook, and Uber are massive and therefore attractive to students. Yu urged Hernandez and similar biotech executives to sponsor research programs and student projects so students would have an easier time developing their passion toward biotechnology and transitioning into the industry.

What are the important qualities or skills to be successful?

Mukherjee advised, when working with people in other fields, be open to criticism, give respect, and try to learn from them. She shared her personal experience working with oncologists as an example. She emphasized the role of the three C’s of being a modern data scientist: computation; communication; and collaboration.

All panelist emphasized the importance of being a life-long learner to keep up with tech innovations and develop interdisciplinary knowledge.

Lightning Talks

The celebration concluded with a networking dinner and lightning talks by sponsors. Industry and academic sponsorship are an important way to support such events and connect statistics and data science professionals within the SFASA community. During the dinner, gold- and silver-level sponsors provided an overview of their business and the role of statistics/data science in the company.