Recommendation Systems Engineer

Recommendation Systems Engineers are data science professionals who develop solutions for driving relevant content and products to users. While you may already be familiar with the concept of a recommendation system from your experiences browsing sites like Amazon or YouTube, these solutions exist in more industries than you might imagine, including healthcare, music, and news. Recommendation Systems Engineers leverage deep data analytics to solve for business goals, and may also work as Data Scientists or Machine Learning Engineers depending on the size and structure of the organization.

What Do Recommendation Systems Engineers Do?

Recommendation Systems Engineers spend much of their time collecting, cleaning, and analyzing data, looking for patterns and insights that can drive better recommendations for users. They will create and deploy recommendation models, measure their effectiveness, and tune them over time, all with the goal of giving users the most relevant and engaging experience possible.

What Skills Do I Need to Succeed as a Recommendation Systems Engineer?

In addition to the mathematical and coding skills common to data science, strong communication skills are essential for Recommendation Systems Engineers. Data analysis and modeling can be complex, so explaining findings to non-technical stakeholders is a vital part of the job.

• Data Analytics
• Machine Learning
• Statistical Modeling
• Software Development (e.g., Python)
• Communication
• Problem Solving
• Critical Thinking

What Projects Can I Do to Prepare for This Career?