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Data Product Owner: job, missions and skills

The role of Data Product Owners is to ensure value comes out of all the data projects of their companies. They need to develop a vision of what the data science team wants to achieve, together with a strategy to get there. Let's talk about their missions and what are the required skills to succeed in this challenging job!

What Is a Data Product Owner? Finding a Vision For the Data and Analytics Roles Of the Business

For every business that uses data in order to better understand their customers and inform their choices, there is an intricate team of professionals who work with that data. There are data scientists, data engineers, data analysts, data miners, and machine learning professionals just to name a few. They all work with different elements of data. In the midst of all of this, however, you need someone who develops and maintains a vision and plan for that data and oversees the execution of that plan. That professional is a data Product Owner.

Owner or Manager: What Does a Data Product Owner Do?

A Data Product Owner serves as sort of a manager to the data science team. The Data Product Owner develops the strategy for the data science team, the vision of what they ultimately want to achieve through use of the data. They implement this strategy and oversee the execution of it throughout the data science team. Because of this, Data Product Owners need to be innovative thinkers as well as good communicators with strong people skills. Some of the responsibilities of a Data Product Owner include:

  • Managing projects across data science and data engineering
  • Coordinating with stakeholders and communicating your vision to them
  • Offering informal and formal coaching to team members
  • Aid the data science team in achieving results

Tools That a Data Product Owner Uses

Data Product Owners must be familiar with the same tools that many of those under their supervision use, so that they can fully understand the processes and issues that might arise within their team. These tools include things like:

  • Programming languages related to data science, such as Python
  • Data architecture structures
  • Machine learning algorithms
  • UX and UI designs
  • Agile frameworks like Scrum

Education and Background

Think you have what it takes to become a Data Product Owner? Let’s talk about education, as well as the necessary experience for the job:

Education Requirements

There are multiple educational approaches you can take to become a Data Product Owner. A 4-year Bachelor’s degree in computer programming or computer science, or a master’s degree in business or in Data Science might give you the edge you need! An intensive bootcamp in Data Science is also a great way to learn all the required skills to succeed as a Data Product Owner. It will equip you with the tools you need and help you develop your network in a short period of time.

Background Requirements

Beyond education, most companies require some level of work experience from candidates before they offer them a job as a Data Product Owner. Project development experience is important, as well as management experience. A work background in data science, data analytics, data engineering or a previous experience in Product Management are helpful to become a Data Product Owner. Usually, companies look for at least a year of experience in a relevant background before hiring.

Ideal Character Traits

It takes a certain kind of person to succeed as a Data Product Owner, especially given their position overseeing data science and data analytics projects. But what kind of person? Some character traits are skills that can be learned, while others come naturally to some people. Here are some of the traits that most companies look for in a Data Product Owner:

Head for Business and Tech Analytics

There are several jobs within big data that need both experience within computer science and within business. Data Product Owners are responsible with developing a vision and plan for the data that the business collects and sharing that with shareholders. For that reason, strong business skills are a must. However, a Data Product Owner won’t be able to make sense of their team without a good understanding of data science.

Finger On the Pulse of Machine Learning and Other Product Advances

Data is an intense industry, with technology and trends evolving more rapidly than just about every other field. Any professional working in data — but especially a Data Product Owner who is responsible for developing that vision for the data teams — should be able to keep up with this fast-growing world. Data Product Owners should be well versed in the latest cloud technology, machine learning advances, and methods for getting the most out of your data.

Owner With Strong Leadership Skills

A Data Product Owner is a manager of sorts, responsible for a whole team. A good Data Product Owner should have a skill for drawing people’s attention and knowing how to delegate tasks and oversee their team. They should be able to be a leader who can give constructive feedback when needed while still being tactful, as well as boosting the morale of their team.

Strong Communication of the Product

Your communication skills tie into your leadership skills, but this is one element that is especially important when it comes to succeeding as a Data Product Owner. As the person responsible for creating a vision for the data and presenting that vision to the stakeholders, a Data Product Owner’s communication skills should be masterful, both written and verbal.

Go With the Flow

There may be structure in the day-to-day of your job as a Data Product Owner, but data is also a constantly shifting industry, which means that you might come in one day and find that the needs for collecting and analyzing that data — or the business’s needs for using that data — have changed. A good Data Product Owner should be able to stay flexible and rise to the occasion.

How Much Money Will You Make In a Year?

If a career as a Data Product Owner sounds like the right call for you, the next question is of course all about financial security. How much will you make in a year? Most careers in data right now are in high demand and are very financially stable if not lucrative. A career as a Data Product Owner is no exception. According to Payscale, the average Product Owner salary in the United States is $85,835, with nearly $7,000 in bonuses and $4,024 in profit sharing.

Of course, your level of experience will impact your pay, as with any other career. The industry in which you work will also make a difference. Many industries can find use for a Data Product Owner, so there will be variety in your choices. The highest paying Data Product Owner jobs seem to be with insurance companies or financial institutions.

Job Satisfaction and Potential Career Paths

For some, the position of Data Product Owner is their dream job. This career includes a strongly above average job satisfaction, with Payscale reviews rating most users as “highly satisfied” with their jobs. However, you might not want to stay in this particular job forever if you’re interested in growing within the field of data. As we’ve established, a Data Product Owner isn’t exactly an “owner” in that they don’t own the business or the data itself, so there is potential to grow from the current position. Some of the positions you might pursue include:

  • Project manager
  • Senior product manager
  • Software product manager

Need Help to Land Your Dream Career and Thrive? How To Become a Data Product Owner

Beyond your work experience, Le Wagon can help equip you with the skills you need to succeed as a Data Product Owner. We have a Data Science course where you can network with peers as well as learn from industry experts. If you have a previous experience in Product Management, our Data Science bootcamp will give you the Data Science skills you need to thrive in your Data Product Owner career.

Ready to become a Data Product Owner ?

Download our syllabus below to discover our Data Science bootcamp and learn more about our alumni and community! You can check out answers to frequently asked questions here.

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