A step-by-step guide to becoming a Data Product Manager

A step-by-step guide to becoming a Data Product Manager

In this blog here, we try to understand the role of data product managers within organizations and how they utilize data science, machine learning, and artificial intelligence to solve problems.

In the rapidly expanding world of today, technology is dominating than ever before. As more and more products become digital, the amount of data generated and collected is increasing, hand-in-hand with the job opportunities peripheral to data.

One role that is on the rise in today’s market around the world — Product Managers. Roles have been growing exponentially and what do you call a role that allows you to manage the product and people while staying close to data? A Data Product Manager — a professional with Data Science & Analytics and Product Management Experience is a huge opportunity!

Over the summer, I discovered a passion for Product Management. I was looking to hone on the skills for a PM and as they said, do a “side project”. As I completed the Product Manager nanodegree from Udacity, I was exploring PM roles in data: responsibilities, skills, products, and tools.

With the increasing amount of data access, Product Managers now have the opportunity to utilize data to advantage by not only enhancing existing products but creating completely new products.

In this blog here, we try to understand the role of data product managers within organizations and how they utilize data science, machine learning, and artificial intelligence to solve problems.

Who is a Data Product Manager?

You are similar to any other product manager, guiding the success of a product and leading the cross-functional teams responsible for improving the product; the addition here: you put data at the heart of everything you do.

Data PMs are responsible for designing products and features based on advanced data-driven insights, visualize data with viz tools for statistical analysis, and identify unique relationships between variables via hypothesis testing and modeling.

Side-note: A good data product manager role would better suit a mid-career role.

product-management data data-science towards-data-science technology

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