“Product manager” has become one of the most lucrative job titles in recent years. The demand for product managers has grown by more than 32 percent in the past two years alone. That’s more than five times faster than overall U.S. job growth. Product manager was listed fourth—just behind data scientist—on GlassDoor’s 50 Best Jobs in America for 2020 list, which factors in job availability, salary and job satisfaction.
Even during the economic slowdown spurred by the COVID-19 pandemic, the job is faring well. Facebook announced in April that it would hire 10,000 new employees, primarily in product management and engineering. Google has stated its strategy is to hire aggressively during the economic downturn, and much of its focus will be on product management. Based on its hiring activity during the previous recession, Apple is expected to follow Google’s hiring strategy.
So, what does a product manager do, and how does the job relate to data science?
The role of a product manager
As the name suggests, the product manager prioritizes and oversees the development of new products for a business. That means working across multiple teams—such as business executives, technical departments, engineers and marketing—to ensure that everyone is working together toward the same product goals. When a new product has been identified, the product manager creates a plan for development, sets a timeline, establishes metrics for product success and ensures that the product fulfills an important need for the customer. Once the product has been launched, the product manager continues to monitor its success, and is the one who is responsible for determining if and when updates or improvements need to be made.
Product managers come to the role in several ways. Many have backgrounds in business or have earned their MBAs. Some work their way up within a company with reputations as problem solvers. Others find specific training courses for product managers. In general, those who are skilled at understanding and explaining problems; can communicate across teams; and have the ability to measure, analyze and present results are well-suited to work as product managers.
Product management and data science
As with many aspects of business development, data science has become a big part of product management. Product managers have to be able to interpret, communicate and make decisions based on data points. Many product management and engineering teams incorporate data scientists, and product managers have to be able to communicate effectively with those data scientists, as well as understand the information data scientist present to them.
Additionally, many business leaders will come forward with problems or products they feel would be something to be worked on by the product or the data science team; product managers need to have enough of an understanding of data science to know which problems can be solved with data, and which problems or projects aren’t well-suited for data science-based solutions. They also need to be able to communicate with business leadership about why (or why not) the data science team should approach a problem as part of a particular product management process.
Finding a job as a product manager
Those searching for a new career—especially if they have experience in project-leading, expertise in a particular domain or a degree in a business field—would find ample opportunity to start and grow a well-paying career in product management. It may just take a little additional knowledge about product management processes or data science, but any training is sure to pay off in this growing field.