Data Science Panel 2020
Video Q&A panel with 5 data scientists working in industry and government.
Attendance: 83 registered, 61 attended, including around 30 students from STAT 128.
Data Scientist was the #1 best job in America from 2016 to 2019, according to Glassdoor.com. Why? What do data scientists do? How do you become a data scientist? Come ask them yourselves at this event, a Q&A panel with 5 data scientists working in industry and government. This panel will be held during our Statistical Computing (STAT 128) class meeting, but all CSU Sacramento students are welcome to attend.
Host: Clark Fitzgerald, Assistant Professor, Math and Statistics Department at CSUS
Panelists:
- Nicholas Alonzo, Data Programmer at CommuniCare Health Centers in Davis, CA
- Hugo Mailhot, Senior Data Scientist at Delphia in Quebec, Canada
- Alejandro Merchan, Research Scientist at California Department of Pesticide Regulation in Sacramento, CA
- Kavi T., Contract Data Scientist at LinkedIn in Sunnyvale, CA
- Brendan Wakefield, Physical Scientist at USGS - California Water Science Center in Sacramento, CA
Agenda:
- 12:00 - speaker introductions
- 12:10 - Q&A with questions from STAT 128 students
- 12:30 - open Q&A
- 12:50 - finish webinar, begin Zoom meeting with breakout rooms for each speaker
Take Aways
Below are some quotes from attendees describing what they took away from the panel.
“The thing that I found the most interesting is how broad this is. I know data science is a big field, but I never realized its even bigger than I originally thought. From this, I feel like many problem I had faced can be solved with data science. I feel like this is a career that can be useful in many other field.”
“Personally, I really appreciated Hugo being transparent about imposter syndrome and how in reality individuals with different backgrounds will shine in other areas of the field. With this variety of archetypes in the field, data scientists are exposed to so many different perspectives in terms of tackling problems; and that the further they are in their field, the more they know and the more they know they don’t. However, as this is a technology-based field, data scientists are continuously learning as technology is constantly evolving.”
“I like the idea of creating a simple visualization to communicate the impact of a project so that recruiters can understand your project without doing a lot of work. The meaning is more important than the complexity. In the chat someone mentioned writing a blog post about your project so that you can share it as a link to employers and I thought that was really smart.”
“Going into the data science panel I wasn’t exactly sure how doing statistical math could be applied to professional fields. My original thought was that these pro’s worked more with data structures, allocating large files in clever ways to save memory space. However the actual application was very nuanced and each panelist worked in different fields working to achieve different goals under the umbrella of data science work. … In summation, what I took away from the data science panel was how diversified the field is and also how passionate the panelists seemed about their jobs.”
“So of the main things I took away from the panel was companies will hire you on communication skill, recommendations, and ability to learn. This was quite a surprise to me since I was under the impression as a Computer Science major that I must know every algorithm and remember every language we went over in class and it was becoming a bit overwhelming. It is more about understanding the concepts and being able to implement the concepts with any resource available to you. (Alejandro) did not know Sql which was a requirement for his job but was hired anyways because his ability to learn, this gave me some hope.”
“I learned that with data science it is continuous learning because there are going to be some tools that they use one day, but then a better tool might come along and then they would have to use that tool instead. A data scientist needs to have a willingness to learn, some things that a data scientist should know is SQL and Python or R. Some career tips that I learned from the data scientists is to try to make a project or to see if I can get an internship or a volunteer position. Overall, this was a great panel and I am very happy that I attended it.”
Questions
Initial Entry / Training
- What kind of entry level data science jobs should I be on the lookout for, if I only have a background in R, SQL, and markdown languages?
- What kind of training is usually required to become a data scientist and what kinds of fields can data scientists work in?
- What would you say are the most desirable attributes in order to be considered for a new hire/intern position?
- What steps can/should a new college graduate take to try to give them an edge when searching for a job in data science?
- What, exactly, do you need to become a data scientist? Education? Experience? Familiarization with data? What can I do as a data scientist, and how would that benefit me?
- What are some recommendations for someone looking into delving into entry level data science jobs, but that’s more on the economic side of things?
- Algorithm optimization plays a massive role in Computer Science when it comes to things like sorting, structuring, and searching big data. Would you say that as a data scientist the role is equally as important? Is it something worth studying immensely, or is it something that is only really required for certain data science fields.
- Where in America and Canada are you most likely to find a high concentration of data science jobs?
- What are some data science certifications available out there? Do you recommend getting certified for an entry job position?
- Many times, an applicant will have basic to little knowledge of any program languages (R, SQL, Java), but are willing to learn (or currently learning). What are some qualifications for you to take interest in these applicants in order to get your attention, or even hire them?
- What background knowledge is required to become a data scientist? Is it possible to get a job in data science with a statistics minor?
Personal Career
- Did you always have an interest in a career in data science or did you come from a different background? How were your experiences during your transition from your initial profession to your current job as a Data Scientist?
- What made you decide to become a Data Scientist? How was this field first introduced to you and what made you take an interest in it?
- What do you enjoy the most about the field of data science? What are the sort of skills(be it technical, foundational, personal) that are sought after in the hiring process of a data scientist position?
- What would you say surprised you the most about data science and the data science community when you first started with your career? What did you find that was either in your favor or a setback?
General Career
- How can you transition your career from software engineering to data science? Are you better of to start out as a software engineer and move to data science or the other way around?
- Are you required to be knowledgeable of an industry before you can successfully analyze it with Data Science? Or is data just data and understanding where the data comes from doesn’t make a difference in its analyzation?
- How related are the fields of data science and machine learning? Do they overlap into each other or is one a subset of the other?
- How many data scientists are usually working on a team together? What different roles do they have and what are the purposes of each role? How do the goals of data scientists change when you are working for different companies? Can you be asked to skew data?
- Is there a route into data science that allows us to continue to work in a given scientific discipline? That is, is there a way for student equality passionate in physics and computer science, for example, to stay active in both fields?
- What are the main differences between a data scientist ,data programmer, data engineer and data analyst?
Other
- How did covid affect the data science field? Is there a lower or higher demand for data scientists?
- Do jobs in Data Science typically come with a lot of overtime?
- Is Data Science a better career path than Actuarial Science? Why?
- What advancements do you expect to happen in the data science field in the next 10 years? What is currently the cutting edge of the field? What does the future of data science look like?
- What’s the largest data set you’ve ever worked with.
- Do most data scientists work remotely?
- What are the most challenging or interesting aspects in the Data Science field?
- How do you think data science is evolving with the social media age where there is so much information out there?
- What kind of math does a data scientist use frequently? What is the most mathematical application you see?