Today’s world is overflowing with data. Due to increased opportunities to gather and store information, business executives can make more informed decisions than ever before. However, to do so, executives must first develop the skills to interpret, understand and draw conclusions from available data.
This ever-growing presence of data is just one reason why “data scientist” is one of the fastest-growing roles in the United States, according to the U.S. Bureau of Labor Statistics. On top of that, by 2030, career opportunities in the data science sector are predicted to increase by 36%. However, not all these positions will be filled by recent data science degree graduates. Instead, many roles could be filled by seasoned professionals in a complementary field: economics.
Professionals with an economics background can transition into data science roles thanks to their preexisting ability to draw conclusions from data sets and clearly present their findings, argues Indeed.com. Economics professionals already have the necessary mathematics and critical-thinking skills and might only need some basic training.
This is why an advanced degree, like a Master of Business Administration (MBA) with a concentration in Applied Business Analytics, is valuable.
Analytics and Economics: What’s the Difference?
Data science deals with dissecting massive data sets using modern tools and techniques to gather actionable insights, which means sifting through data to help guide decision-making. Many people wrongly associate data science with a computer engineer or coder. While this is one facet of the role in the field, it’s far from the entire picture.
On the other hand, economics is a branch of knowledge concerned with the production, consumption and transfer of wealth. In a similar style to data science, economists often dive into immense data sets to uncover insights. However, while they may lack the coding training of a data scientist, economics have an advantage in communicating their findings to others.
Both economics and data science are rooted in statistics, require strong analytical skills and typically solve quantitative problems using modeling. However, the two professions are usually interested in finding different answers from a data set.
For example, let’s say that an economist and a data scientist receive a large data set of commercial loans and supplementary information. The economist would likely be most interested in understanding the main factors that increase the credit risk of commercial loans. On the other hand, the data scientist would likely want to determine something like what the best models are to predict the credit risk of commercial loans.
To use Cambridge Spark’s words, “the economist focuses on causality, whereas the data scientist focuses on prediction,” but both aim to meet statistical assumptions.
Why Transition to Data Science?
If you’re a recent graduate with a background in economics, why would you consider transitioning to data science?
While data science roles are growing in demand, data scientists are also very highly compensated employees. In 2021, the annual median wage of data scientists was $100,910. As the need for data scientists grows, it’s safe to assume that this compensation will trend up and to the right.
Additionally, economists may find that data science is already seeping into their work areas. For example, data science is prevalent in sectors such as banking, finance, public policy, consulting and even public sector work like economic development.
Elevating Your Conversations
Thanks to the prevalence of big data in today’s world, business conversations will continue growing increasingly more complex. This is because, pending a technological disaster, businesses will continue leveraging as much data as possible to fuel decision-making.
For recent graduates, this means you must have satisfactory data comprehension and quantitative analysis skills. For middle/senior managers, you’ll need to better understand the world’s economic systems and how they impact your business.
Anyone who aspires to enter a managerial role will need to become proficient in data analytics to some extent. Luckily, for those with a history in economics, this could be a fairly simple transition. One of the best ways to transition is to obtain an advanced degree.
For example, William Paterson University offers an online MBA program with a course titled Economic Analysis for Decision-Makers. This course dives into the micro and macroeconomic forces that form our economy, such as supply/demand, revenue/cost and regulations/taxation. This course further discusses the impact of these forces on production, consumption and the economy as a whole. For anyone looking to enter the world where economics and data science collide, an advanced business degree with a focus on applied business analytics might be the perfect path for you.
Learn more about William Paterson University’s online MBA with a concentration in Applied Business Analytics.
