Data science product management can be a rewarding yet complex career path.
As a data science product manager, each new product you oversee will be different. Each project will be unique, with its own set of challenges that you need to overcome as well as its own problems that to be solved.
If you choose to follow this path, you will have a lot of pressure on your shoulders. Cross-functional teams will be looking to you to lead the way and keep the product roadmap moving along.
It’s a challenge, and you’ll need a select set of skills in order to face up to it. This will include not only an expert-level understanding of data science itself but also a range of soft skills and managerial skills that will be necessary along the way.
If you’re ready to learn more, this guide will go over ten of the most important skills you will have to master in order to succeed. We’ll describe each skill in detail. We will also look at some tips and tricks you can use to acquire and improve these skills.
To learn more via video, watch below. Otherwise, skip ahead.
1. Data Science Skills
Let’s begin with one of the most important skills that all data science product managers need to have, which is a deep understanding of data science.
If you hope to be put in charge of data-related projects, you need to know data science inside and out. You’ll have to be a master of data collection, data set analysis, data interpretation, and much more. You’ll need to know real-world applications of data and keep abreast with the latest data trends.
The knowledge you have of data science will be vital when it comes to understanding why a new product is being made, as well as spotting the market trends and customer needs for the product you’re managing.
Plus, throughout the product development cycle, being an expert in data will help you overcome problems along the way, make necessary changes or improvements to the initial roadmap, and keep all of your technical teams on board and up-to-date.
The best way to sharpen your data science skills is by way of a professional course. Educational courses on technical product management can teach you all you need to know to become the best possible PM.
2. Management Skills
The managerial aspect of being a data science product manager is a facet of the job that prospective professionals should never take for granted. As a data science PM, you will be placed in charge of various teams and charged with organizing those teams, managing multiple workers, and being the main go-to person for problem-solving and organization.
Again, that can be a lot to take in, and many new challenges might present themselves on a day-to-day basis when working in this position. It will be up to you to overcome those challenges, relying on your managerial skills to help you. Such skills include
Therefore, if you want to succeed in this role, you’ll need to be a very strong and dependable manager. You’ll need to keep a cool head when things go wrong in order to solve problems. You’ll also have to demonstrate excellent communication and leadership to help your teams move forward and prevent the project from derailing or taking longer than necessary.
There are plenty of ways you can work on these skills. A good method is to get some experience in the world of management. You don’t have to dive right into product management. Even something as simple as working in a managerial position in a standard office or retail environment can help you build up your management skills.
Another good way to strengthen your managerial standing is through education. Once again, there are various courses online that can help to teach you the management skills you need. Our Product HQ Product Manager Course is a great option to help you build up the abilities you need to manage teams.
3. Communication Skills
It doesn’t matter whether you’re an AI product manager, a machine learning product manager, a fashion product manager, or a data science manager; in this line of work, communication is key.
You won’t have to handle entire projects alone. In fact, a typical project may have different workers spread out across different teams.
These teams will all need to communicate with one another, and product managers are a vital piece of the communication process. They facilitate communication between teams, ensuring that everyone is on the same page and up to date with the latest developments in the project.
A lack of communication can lead to all sorts of issues:
- Delays to the product schedule
- Wasted time working on things that are unnecessary or no longer needed
- Decreases in team morale due to miscommunication
- Disappointment among stakeholders due to interruptions in the development cycle
- A failed product launch
- A product that does not meet the expected standards, with missing features or broken functions
From this, it’s clear to see just how important communication can be. It’s up to the PM to be the project’s lead communicator, talking to teams, stakeholders, customers, and more.
You will therefore need to work on optimizing your ability to communicate in a clear and effective manner. Plus, since you’ll be talking to different groups of people, you need to adapt your approach accordingly to suit your audience.
Communication strategy frameworks, like the one pictured above, can be helpful in terms of structuring your approach and finding the right questions to ask and subjects to discuss.
4. Researching Skills
Research is an integral part of the data science product development process. Before development even begins on a new product, research needs to take place in order to find out things like current market trends, customer needs, and so on. Research is invaluable in terms of finding ideas for products that can be developed and have a strong chance of being successful and useful in the real world.
As a data product manager, here are just some of the things you may need to research:
- Existing trends in the data science space
- Needs and desires of customers
- Products and projects of rival companies that could compete with your future products
The world of data science is fast-moving and ever-evolving. You’ll need to stay informed and up-to-date on the latest developments. Hopeful data science PMs, therefore, need to exhibit strong research abilities. You need to make use of multiple resources to find information in a rapid and efficient manner. This is something you can work on in your own time by finding trusted research tools and resources online.
5. Business Skills
In the past, product managers didn’t need to know much about business metrics. They were only responsible for overseeing the development of a product. They didn’t have to worry about how viable it was for the existing market of the time.
In today’s world, however, product management has evolved. One of the biggest changes that we’ve seen is that modern PMs are expected to have a good grasp of business sense; they need to understand why a product is being made from a business point of view, with a keen knowledge of the market and a thorough understanding of client expectations.
This means that if you want to become a data PM nowadays, you’ve got to have a good mind for business. You can’t be concerned with how to manage product development if you don’t understand why businesses need this process. You must know about the potential of a product to impact a company’s standing, finances, profit margins, and more.
If you feel that you are lacking in business knowledge, there are ways to improve this. Business studies courses and certifications can help to bolster your grasp of business fundamentals. You can also learn more about business by working on more and more data science projects in other areas aside from management.
6. Data Analytical Skills
Of course, if you want to work in the world of data scientists, you need to be an expert in reading data and finding insights through accurate interpretation.
This is key in any kind of data-related role, as the whole concept of data science is about taking big amounts of data and extracting useful information from it.
However, the skills of data reading are even more important when you’re in a managerial role. This is because you may have to interpret various kinds of data during the product lifecycle. This includes everything from market data to inform your initial product designs to business data that can help you plan out the product roadmap.
Interpreting performance metrics can also be important, as it will help you optimize your product development business processes and keep your teams on track.
You’ll be reading data non-stop while managing the development of different products. What’s more, you’ll use the information you find to make critical decisions throughout the process. Therefore, you need to be proficient at seeing trends in data and breaking them down.
The best way to build up your data analysis skills is through education. Courses in statistical and analytical skills can be found online to help you improve. You can also spend time working firsthand with analytical experts to find out more about how they operate and pick up some new techniques.
7. Delegation Skills
As a product management professional, you’ll be in charge of multiple teams. Different people will be working under you and there will be a lot of different tasks to get done. Most times, people will look to you to make decisions about which tasks are finished first and which teams or workers carry out those tasks. In other words, you’ll need to do a lot of delegating.
Delegation can seem simple from the outside. However, when you’re in a position of having to quickly and accurately delegate multiple tasks and roles across multiple teams all at once, it can get complicated. And a single mistake could spell disaster for the project. After all, putting the wrong people on the wrong tasks could lead to delays, problems, mistakes, and more.
This is why it’s wise to work on improving your delegation abilities.
8. Marketing Skills
Today’s product managers don’t only need to know how to develop products and oversee the development. They also need to understand the business side of the project and play an active role in helping the product get sold and become successful.
A data science PM will need to be involved in the process of marketing the products they help to make. They’ll need to understand concepts like branding strategies, sales meetings, lead generation, and how to communicate with possible customers.
Therefore, you’ll also have to ensure that you have strong marketing skills. Again, you can make use of educational online courses to improve in this area. You can also work with marketing professionals and teams to learn more about how they operate and keep up with the latest marketing and sales trends.
9. Scheduling Skills
The average day of a data science product manager can be filled with a wide range of tasks that need to be done and unexpected challenges that can arise without a moment’s notice. It is therefore imperative that you know how to pick priorities and schedule your tasks and your team’s tasks in an efficient manner.
A dependable product management professional should never be overwhelmed or intimidated by a long list of tasks or challenges. They should see what needs to be done, identify the most important tasks, and get their whole team organized.
You can improve your power of prioritization and scheduling by getting as much experience as possible. The more often you find yourself having to schedule and prioritize, the better you can become at it.
You can also take inspiration from other managers and people in positions of power that you encounter over the course of your career. Observe them and see how they respond when faced with a mountain of tasks and challenges. You may be able to learn a lot from their responses.
10. Problem-Solving Skills
Data science projects often start off with a nice, neat product roadmap. Everyone begins with a clear vision of the final product and defined expectations of how the development process will go. However, things often don’t turn out the way we expect in this line of work.
As the process goes on, all sorts of unexpected problems can arise. You might find that your initial budget is inadequate, for example. Team progress can also be halted or interrupted due to unforeseen circumstances, or a rival company could launch a similar product before you. All of this implies that you need to make changes prior to your launch.
When these kinds of problems appear, it’s up to the product manager to find ways to solve them. Others will help out, but you will be the primary problem solver of the entire process. You need to be able to think in a strategic way. This entails adapting to changing conditions and facing difficult situations head-on.
Over time, you will learn how to maneuver the challenges of being a data science product manager. Taking educational courses will assist with your strategic and dynamic thinking abilities and help you be a force in the field.