October 2022 National Student Data Corps Data Science Career Panel


Guest Post: Hazel Mbambo

A recording of this event is available at the Northeast Big Data Hub’s YouTube channel.


On October 19th, 2022, the National Student Data Corps (NSDC) hosted the first National Hispanic Heritage Month Data Science Panel. Florence Hudson, the Executive Director of the Northeast Big Data Innovation Hub (NEBDHub), began the event by welcoming the co-moderators, the panelists, and the attendees. The event was co-moderated by Raul Cosio and Isabella Graham Martinez. Raul is a retired IBM Vice President and has received awards from the Hispanic Engineer National Achievement Awards Corporation (HENAAC) and the Society of Hispanic Professional Engineers (SHPE). Isabella is a full-time student at Columbia University, works part-time at the NEBDHub as a Project Coordinator, and is a National Hispanic Scholar Awardee.

The panel included Ashley Atkins, the Executive Director of the West Big Data Innovation Hub; Fred Uquillas, a fourth year Ph.D. student in neuroscience at Princeton University and the Founder of NeurOn; and Gabriela Cavazos, an undergraduate research coordinator at Laredo College.

To open the conversation, Florence spoke about the NEBDHub’s Hispanic community, stating that a large number of the NEBDHub’s student community is from Hispanic-serving Institutions or located in Spanish-speaking countries. We then heard from Isabella, who shared information about the NSDC’s educational programming and resources, which include the Learner Central, Educator Central, Video Library, Chapter Central, and Career Central

Raul kicked off the panel by asking the panelists to share their backgrounds and history in the data science field. We first heard from Ashley, a hydrologist who became interested in water research and data because of her family’s strong Hispanic roots in New Mexico. Fred then spoke about his time at UC Berkeley and his passion for graph theory methods, a set of mathematical tools used to assess relational networks. This led him to a particular interest in neuroscience. He did a presentation at the Annual Biomedical Research Conference for Minoritized Scientists (ABRCMS) and fell in love with statistics and data science.

Gabby followed the discussion with anecdotes about her first exploration of data science. During an internship she held at the USDA Agricultural Research Service, she learned how to collect data and analyze it herself. Now, she works as a research coordinator at Laredo College and is a Co-Principal Investigator for the NSF RAPID grant: “Using Real Life COVID-19 Data to Teach Quantitative Reasoning Skills to Undergraduate Hispanic STEM Students.

The panelists were then asked to describe any resources or programs they found helpful in their early data science careers. Fred shared that lab fellowships were useful for gaining a foothold in the field. He encouraged attendees to explore offerings at the National Science Foundation and the National Academy of Sciences. Gabby then explained how helpful mentors can be in your educational and professional pathways. She also recommended the Hispanic Association of Colleges and Universities (HACU) Conference to students wanting to find internship opportunities. Ashley credited experiences that challenged her to think outside the box. She values those experiences because data science requires a lot of innovation and adaptability. Raul added his insight that the most important aspect of career development is aligning and listening to people that you respect. During his time at IBM, he found that the best executives and managers always encouraged him to take risks and challenge himself. Prompted by Raul, Isabella shared that, as a student, mentors have been instrumental to her progress.

The panelists were then asked about which software programs were most used in their daily roles. Gabby uses Mendeley, SPSS, Excel, and R Studio for coding. Ashley uses a lot of system-science methodology tools specific to her field such as Vensim, while Fred recommended R for coding and the My Study Life application for scheduling.

Raul asked the panelists what soft skills are most important for success in the data science field. For Ashley, data scientists need to be excellent communicators, regardless of how technical their jobs are. Gabriella echoed Ashley’s response and added that teamwork was a crucial skill. Fred advised not taking on too much and knowing how to delegate tasks well. 

When asked how they expect data science to change in the coming years, the panelists shared a variety of perspectives. Fred said he believes Artificial Intelligence (AI) will allow more freedom of time and thought. Gabby encouraged students to keep their knowledge current by taking free workshops. Ashley thinks the field will grow and combine with other existing fields which will increasingly adapt data science methodologies. 

The panelists were asked how they would recommend students begin a career in data science and scientific research. Gabby advised that students ask faculty for research and support opportunities. She also recommended applying for internships like those through the USDA Pathways Recent Graduates Program. Ashley advised students to develop long-term goals and work backwards, finding valuable opportunities that match their goals along the way. Fred’s answer was to learn how to code. He highlighted a book called Discovering Statistics Using R by Andy Field as a helpful resource. For management skills, he recommended a book called Multipliers by Liz Wiseman. Raul encouraged risk-taking and exploring unfamiliar areas before closing the panel discussion.

The panelists and moderators then fielded questions from the live audience. We learned from the speakers that it is best to be open to unexpected challenges and opportunities, take on internships where you can, and to have a dual focus on hard and soft skills. Emphasis was given to the importance of the Hispanic community in the data science field.  

The panel closed with a general thank you to all panelists, moderators, and facilitators.


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