Have you ever wondered how Netflix tailors its recommendations to suit your tastes? In this article, we zoom in on a career that blends computer science, mathematics, and business: data science, where the analysis goes deeper than you might think.
In the age of information, where data streams from rain gauge measurements, internet outages, and social media interactions form vast reservoirs, the role of a data scientist becomes paramount. These professionals serve as skilled interpreters, extracting meaningful insights to inform decision-making across diverse industries.
Data scientists, utilizing advanced software and statistical methods, play a pivotal role across industries like health care, information security, manufacturing, agriculture, economics, and the sciences. Data scientists often find their work closely aligned with the career bubble of information technology. For example, in health care, they sift through patient data to derive insights for hospitals and healthcare associations. Beyond traditional methods, data scientists leverage programming and machine learning to create predictive models, aiding in informed forecasting. However, their work goes beyond revelation; they meticulously scrutinize data, rectify errors, and ensure the accuracy of their findings, reinforcing the reliability of their conclusions.
A minimum of a bachelor’s degree, typically taking four years, is required for a career in data science. Relevant fields include data science, mathematics, statistics, computer science, and computer engineering. Many employers prefer candidates with a master’s degree (1 to 2 years), and some data scientists hold Ph.D. qualifications (4 to 5 years). Some professionals in the field also come from related areas like health sciences or agriculture.
Furthermore, high school preparation is essential. Taking challenging math, computer science, and statistics courses is advised, along with gaining experience in computer programming. Relevant certifications include CAP, Microsoft Certified: Azure Data Scientist Associate, and IBM Data Science Professional Certificate. Additional training can be obtained through data science boot camps, online courses, and continuous learning in workshops and conferences to stay abreast of industry advancements.
Data scientists are primarily responsible for analyzing and interpreting statistical data, utilizing various sources such as the internet, databases, and publications to gather information. They employ computer models to collect and interpret data, present their findings, and actively seek opportunities to enhance productivity and optimize data handling processes.
Some of the main trends in data science include Artificial Intelligence and Cloud and Data-as-a-service. In business analytics, AI enhances accuracy in predictions, streamlines mundane tasks like data gathering and cleansing, and empowers diverse workforces to act on data-driven insights. AI, particularly through machine learning (ML), enables rapid data analysis and insight extraction through continuously improving software algorithms. Cloud technology forms the essential platform for data-as-a-service (DaaS), allowing companies to access curated data sources through pay-as-you-go or subscription-based cloud services. This eliminates the need for companies to build expensive data collection systems. DaaS not only provides raw data but also offers analytics tools as a service, enriching insights by augmenting a company’s proprietary data.
Srinivas Nelakuditi is a senior Data Scientist at a leading, revolutionary company called Data Bricks. He previously worked as a software engineer at JP Morgan Chase. When asked why he changed fields to become a data scientist he described a “technology shift” stating that “technology is rapidly developing with so much more data being created. I just got the jump and switched to data science before everyone. With this rapid progression, people will also need to progress or be left behind and have their jobs become obsolete.”
Data scientists are employed by a variety of organizations, including governments and private companies. Their work is typically conducted indoors in office settings, involving prolonged periods of sitting and keyboard use, which may lead to strain on the neck, hands, wrists, and back, and may result in conditions like carpal tunnel syndrome. To mitigate these risks, ergonomic chairs and keyboards are utilized for enhanced comfort, and some companies offer posture training and exercise breaks. Data scientists generally adhere to a standard 40-hour workweek but may need to follow strict schedules, occasionally requiring evening or weekend work to meet deadlines.
Overall, data science stands at the forefront of innovation, revolutionizing industries by extracting meaningful insights from the wealth of available information. If you have an aptitude for mathematics and coding, then this might be the profession for you!
Works Cited
Marr, Bernard. “The Top 5 Data Science and Analytics Trends in 2023.” Forbes, 31 Oct. 2022, www.forbes.com/sites/bernardmarr/2022/10/31/the-top-5-data-science-and-analytics-trends-in-2023/?sh=51ad92215c41. Accessed 12 Nov. 2023.
“Data Scientist.” Xello, student.xello.world/options/career/1119/?uuid=1d55c37b-bb43-4c35-9b37-a273a11ff553. Accessed 12 Nov. 2023.