Montgomery College, Rockville Campus, hosts the Data Scientist Speaker Series, where they discuss data science and the people who practice it professionally. On February  17th, the Data Scientist Speaker Series had a discussion where they brought four different panelists and faculty members to discuss what data scientists do. Essentially, what challenges do they face daily, and why should the reasons for MC students study data science?

In recent years, the term data scientist has gained popularity. Many companies and institutions seek data scientists to offer their services; as a result, many people have considered getting a job in this field. What do data scientists do? To answer this question, we must first examine data science as a field of study.

By definition, data science examines information, also known as data, obtained from any source, such as finance, market analysis, among others. The researchers in the discipline analyze how to implement it for peoples’ benefit. This science uses principles from mathematical analysis to perform their studies, and nowadays, data scientists also implement computer science and programming principles to improve their performance.

Danny Zang, a data scientist working at AstraZeneca; Dr. Adbi Mohamed, data scientist and AI ambassador at SAP; Michael Lapucci, director at Simplify Compliance; and Ram Balasubramanian, a data scientist consultant; spoke as guests at the event. Also, Professor Rachel Saidi attended as the moderator of the panel for this talk and conducted most of the questions for the data scientists.

“What is an interesting problem or question that you saw in the data science space?” asked Professor Rachel Saidi to open the discussion. Lapalucci explained, “One of the problems that we faced is understanding our marketplace in different moments (…), we sell products that help people to regulate their medical expenses. Basically, we have to understand what is our market penetration, and it can be challenging for people to do that. I built a simple model that makes a fuzzy match using medical industries from different positions. Using our client’s information, we can rank the most convenient places for them to get their medical attention.”

Similar to the example Lapalucci stated, data scientists have the skill to make the data analysis process more efficient for companies and institutions. This reason primarily demonstrates why companies and institutions are interested in having them in their teams.

As the discussion continued, Professor Rachel Saidi asked the four guests, “what levels of credentialing in data scientist a student in Montgomery College or somewhere else would need to get into your organization?”

Balasubramanian answered, “The number one quality that I would say is curiosity, to think about why things are the way they are, and most still, how I am to answer a question that is difficult to ask, and from there, how to break down a problem and analyze its components. The second one is very hard technical skills, coding skills, and database skills to get and analyze data. The third one I would say is tenacity; there is a joke that says, ‘80% of a data scientist’s job is data preparation, and the remaining 20% is complaining about data preparation.’ data scientists have to be prepared to face immense amounts of data in order to get to the underline problem and the answers.”

The four guests agreed data science has existed in society for most of humanity. People analyzed data from ancient times up until the present day. However, as human societies start to grow, the data people must handle grows exponentially.

Due to its importance nowadays, the field has gained many prospective members. Thus, interested students have the opportunity to get data science skills at Montgomery College through classes and resources.

Students who are interested in learning more about Data Science at Montgomery College can find more information here: https://www.montgomerycollege.edu/academics/programs/data-science/index.html