Machine learning is becoming a crucial part of all businesses as we move toward a more technological and automated future. That’s why job titles like Machine Learning Product Manager have popped up.
AI, deep learning, and machine learning are constantly being taken advantage of by companies as data science takes the wheel of contemporary business practices. They rely heavily on the abundance of data these days.
The truth is, leveraging machine learning and AI is more efficient, quicker, and more effective than relying on the human mind. That doesn’t offset the importance of human employees, it just gives them better tools to work with.
In this article, we’ll go over what a machine learning product manager is, their roles, responsibilities, skills, and more.
Let’s get started.
Table of Contents
What Exactly is a Machine Learning Product Manager?
Starting off, you need to understand the difference between machine learning and AI. In most cases, both terms are used interchangeably, but AI is a broader term. In fact, machine learning is a subset of AI that focuses on enabling machines to learn for themselves.
Machine learning entails the structuring and classification of data to develop feedback loops that are used to make predictions and decisions without human input. However, to make it work, a human has to develop machine learning algorithms and machine learning models.
That’s why a machine learning engineer’s job can’t be automated. It involves tons of statistics and datasets that are used to develop training data that helps set up the initial systems.
Typically, a product manager that understands the nuances of machine learning can become a machine learning product manager. However, in most cases, you need to be able to work with ML models and algorithms to be considered one.
Machine Learning Product Manager Typical Roles in Organizations
Machine learning product managers can have multiple roles within any organization depending on the industry, size of the company, and product lines. In all cases, they work closely with various product teams, development teams, engineering teams, and other stakeholders.
Their roles can be summed down to the following aspects:
- Data Literacy – It’s crucial for ML product managers to be literate about all things data. That includes machine learning concepts, basic AI concepts, and data science fundamentals. They need that understanding to evaluate data, ask the right questions about said data, and more.
- Problem Mapping – All ML product managers need to be able to figure out present problems and how many of them can be solved using machine learning. You can’t solve all your problems and issues using machine learning. Therefore, a machine learning product manager must be able to distinguish those problems.
- Explainability – You need to be able to explain complex machine learning processes in simple terms when communicating with customers, upper management, and other stakeholders. Machine learning is extremely technical and can be hard to understand for an average Joe, and that’s why ML PMs have to be good with explaining ML processes.
- Acceptance Criteria – Another role of an ML PM is that they have to determine what things need their attention. That’s because this helps them set up their machine learning algorithms and models. The ideal way to do that is to create robust acceptance criteria for acceptable outcomes. That helps refine the quality of the results.
- Communication – ML product managers need to work closely with all other teams to ensure their ML processes are understood and working.
Based on the roles listed above, machine learning product managers have clearly defined duties, responsibilities, and tasks.
Machine Learning Product Duties and Tasks
The duties, tasks, and responsibilities of a machine learning product manager can vary based on their roles. It mostly depends on the industry, products, product types, and the organization.
However, there are a few duties and responsibilities that are expected from all machine learning product managers. They should be able to:
- Oversee various products, product lines, and manage production
- Work on the product roadmap based on the product lifecycle.
- Assist the product team in the development, creation, and management of new products to ensure that they become successful products.
- Help the product owner and development team in the product development process by doing relevant data analysis.
- Collaborate with internal teams and external partners to work on delivering various AI/ML solutions to meet customer needs.
- Work closely with the engineering teams and product leaders to ensure everything is being developed and managed accordingly.
- Define data and annotation strategies for all machine learning projects.
- Take an active part in sprint planning, retrospective activities, and backlog review and prioritization.
- Monitor open bugs, missing data, output precision issues, and result incompleteness and inconsistency.
- Ensure that all the requirements for ML capabilities are fulfilled. Furthermore, oversee the development, management, and maintenance of multiple ML pipelines and tools.
- Work with various teams to test machine learning models frequently to ensure they work and accelerate time-to-market based on real-world estimates.
- Identify the right use cases for machine learning, including business cases.
- Weed out internal biases while testing new data to develop better product functionality.
- Decide on the product feature tradeoffs based on the user experience data.
- Evaluate what metrics need to be tracked to improve machine learning models.
- Identify new business opportunities that can utilize AI/ML technology to drive profitability.
The duties and responsibilities listed above are true for all machine learning product managers.
If you're interested in learning what it takes to excel as a Machine Learning Product Manager, then check out our certification courses.
Machine Learning Product Manager Skills and Abilities
The skills and abilities of a machine learning product manager are usually the same across all industries. However, there are some industries that require industry-specific skills because they’re crucial to the job.
Other than that, some companies also require ML product managers to have additional skills and specialization to work with their products.
In any case, the following are the skills and abilities that all machine learning product managers should possess:
- A complete understanding of machine learning concepts, machine learning models, and algorithms.
- Fundamental understanding of AI and other specialized concepts like deep learning.
- Complete understanding of various machine learning branches, such as supervised learning, unsupervised learning, federated learning, active learning, reinforcement learning, transfer learning, multi-task learning, and meta-learning.
- Ability to ask the right questions about any idea using ML knowledge.
- Consistent ability to remain user-centric at all times by focusing on customer needs.
- Good understanding of various mathematical and statistical concepts such as regression.
- A great understanding of data science and machine learning lifecycles.
- A basic understanding of common programming languages, such as Python.
- Excellent quantitative skills, along with strong analytical skills.
- Superior interpersonal and communication skills.
- Leadership skills to effectively collaborate with and manage multiple teams.
- Good planning, time management, and organizational skills.
- Detail-oriented and execution-focused approach.
The skills and abilities listed above are required by all companies, despite their specialization.
What Does a Machine Learning Product Manager Do – Typical Qualifications
The qualifications of a machine learning product manager can vary depending on what industry and organization they work with. However, what’s more important is their career path. It’s possible to be a machine learning engineer and become an ML PM. Similarly, a product manager can learn machine learning to become an ML PM too.
Despite what career path you take, all machine learning product managers are expected to have the following qualifications:
- A bachelor’s degree in product management, business administration, machine learning, data science, or any related field.
- A Master’s degree in the same field is not necessary but may be preferred by some organizations.
- At least five or more years of work experience in product management using machine learning.
- Background in data science, product management, machine learning, or AI.
- Qualified to use various Microsoft Office software, Gmail, and other important tools.
- Strong understanding of SCRUM and agile methodologies.
- Relevant certifications in product management, machine learning, data science, and other disciplines.
The qualifications listed above are required by most companies. However, some companies may require additional qualifications based on their product lines and industry.
How to Become a Machine Learning Product Manager
Becoming a machine learning product manager takes a lot of time because you’re essentially mastering two different things at the same time. Meanwhile, you’re also learning how to integrate both of them into a single role. It’s safe to say that it’s not an easy job and that not everyone can handle it.
That’s why the machine learning product manager salary is higher than the average PM salary. According to Glassdoor, the average AI/machine learning product manager salary in the US is around $111,637. The typical salary range is between $71,000 and $177,000, with the higher end being offered in cities like San Francisco and New York.
The salary tends to vary on a lot of things like the location, industry, and organization you’re associated with. For example, a machine learning product manager at Netflix or Amazon earns a lot more than an ML PM working in a startup.
Other than that, the roles, responsibilities, and duties can also vary depending on the organization and industry. More specialized roles tend to pay higher but also require additional qualifications and skills.
Therefore, it can take years to get to the point where you’re experienced enough to work with both product management and machine learning. However, in any case, you need to learn product management first and then move on to machine learning. You can start by reading product management books.
It’s also best to do some product management certifications and courses to get certified. When you’re done, you can start your PM career in any organization. Work on things like product strategy, product vision, and try to work your way up to the product manager position.
Once you’re there, you can start by learning or utilizing your machine learning knowledge. After a while, apply to become a machine learning product manager.
Becoming a Great Machine Learning Product Manager
The machine learning product manager job requires a great deal of expertise, whether it’s a software product, retail product, or any other kind of product. Becoming a great machine learning product manager is all about getting as much experience as possible.
That includes experience in product management and machine learning alike. If you have a clear understanding of both and are able to utilize them together, you’re already on your way.
If you’re upskilling using certifications and courses, update your progress on your LinkedIn profile, CV, and website (if you have one).
Continue doing this to slowly and surely become a great machine learning product manager.
Frequently Asked Questions (FAQs)
1. What is a machine learning product manager?
A machine learning product manager is someone who has all the roles and responsibilities of a typical product manager combined with the skills and abilities of a machine learning expert. ML Product managers need a deep understanding of data science, mathematics, statistics, and other concepts like deep learning and artificial intelligence.
Using their data science knowledge, they tend to make product management more efficient. They mostly do that by employing and leveraging data science tools, machine learning models, and algorithms to automate product processes, get better evaluations, and extrapolate crucial insights.
Alternatively, various SaaS and IT companies that have products and services leverage machine learning and data science to hire machine learning product managers. That’s mostly because a ML PM is the best of both worlds. They understand product management while also having a good idea of how machine learning fits into the equation.
2. How do I become an AI product manager?
Becoming an AI product manager is easy if you have experience with product management. That’s because the first step to becoming an AI product manager is to become a PM. Once you’ve had enough experience as a product manager, you can choose your AI application domain. Gain additional knowledge of it and learn to develop AI systems and maintain them. Once you’ve got that down, you can tie that with your product management experience to become an AI product manager.
However, keep in mind that while you can master product management with enough experience, mastering AI is a whole other story. You need specialized education while practicing AI concepts for weeks at times. If you’re trying to learn about AI for free, it’s best to opt for various online courses and certifications. That not only helps you to learn but also helps you to certify your experience.
Other than that, you can also join one of many data analytics boot camps to get an all-in-one learning experience.
3. What does an AI product manager do?
An AI product manager is someone who has all the roles and responsibilities of a typical product manager tied with the skills and abilities of an AI expert. AI product managers need a deep understanding of artificial intelligence, data science, computer science, and other concepts like deep learning and machine learning.
AI product managers mostly work on creating, improving, and enhancing products using artificial intelligence and ML models. Most companies today have AI initiatives that make use of large data sets, machine learning algorithms, neural networks, and statistical concepts like regression.
An AI product manager usually works with machine learning engineers, data scientists, product leaders, and senior product managers. AI PMs mostly focus on the application of AI initiatives in product management, ensuring greater efficiency, productivity, and quality.
4. What is a machine learning product?
A machine learning product is any product that utilizes the power of machine learning and AI. It uses the machine learning application, ML models, and features that help provide predictions based on existing data. ML products use a lot of raw data and are usually developed and managed on the foundation of strong machine learning concepts.
Machine learning product managers tend to manage these ML products by making use of their product management and ML expertise. In the long run, machine learning products undergo constant improvements and enhancements.
Furthermore, most MVPs (minimum viable products) today tend to be machine learning products due to their reliance on real-time data.
5. Will AI replace product managers?
According to Replaced by Robot, a website dedicated to explaining how likely it is for a job to be taken over by a robot, there’s a 0.41% chance of automation for the product manager job. Out of 702 jobs, the product manager job is ranked at #14, making it one of the most unlikely jobs to be automated.