Preparing for an interview at Samsung Ads requires a multi-faceted approach. You must demonstrate that you are not only a skilled product strategist but also a highly technical partner to engineering and data science teams. Start by reviewing the core mechanics of programmatic advertising, and practice structuring your answers using frameworks that highlight your analytical and metrics-driven mindset.

We recommend focusing your preparation on these key evaluation criteria:

Domain Expertise (Ad Tech & CTV) – You must prove a deep, hands-on understanding of ad servers, bidding platforms, SSPs, DSPs, and the unique nuances of Connected TV. Be ready to discuss industry standards, protocols, and monetization metrics.

Analytical Rigor & Data-Driven Decision Making – Your interviewers will look for strong quantitative skills. You should be comfortable discussing SQL, APIs, experiment design, and data analysis using BI platforms to prove your hypotheses.

Strategic Problem Solving – You will be evaluated on your ability to break down highly complex, ambiguous software product management case studies. Focus on structured frameworks that demonstrate clear prioritization and trade-off management.

Stakeholder Navigation & Communication – Because Samsung Ads operates globally, you must show that you can lead cross-functional teams with humility, manage conflicting priorities, and clearly communicate technical concepts to non-technical stakeholders and senior executives.

The interview process at Samsung Ads is comprehensive and designed to thoroughly evaluate your technical capabilities, strategic thinking, and cultural alignment. Depending on the seniority of the role and the specific location, the process can range from moderately structured to highly intense. Candidates should prepare for a multi-stage journey that tests both theoretical knowledge and practical execution.

The process typically begins with an initial phone screen or scoping interview with a recruiter or team member to assess your career history and high-level fit. This is followed by deeper technical and strategic rounds, which often include a panel interview, a director-level case study discussion, or a structured assessment centre. In certain regions, you may be asked to complete a take-home task or prepare a strategic presentation to deliver to a panel of interviewers.

The timeline above outlines the standard progression of the interview stages for a product management candidate. You should use this sequence to pace your preparation, ensuring you master high-level domain concepts before diving into deep case study and presentation prep. Be aware that the exact timeline and requirements can vary depending on whether you are interviewing for regional offices or the global headquarters.

To stand out during your Samsung Ads interviews, you must understand the specific competencies your interviewers are looking for. Here is a deep dive into the primary evaluation areas.

Ad Tech & Ad Serving Mechanics

This area evaluates your operational knowledge of the programmatic ecosystem and your ability to build scalable technologies that govern how brands and audiences are matched.

Be ready to go over:

• Pacing and Delivery – How ad servers distribute impressions evenly over a campaign's lifetime.
• Supply Path Optimization (SPO) – Strategies to streamline the path between buyers and sellers to maximize efficiency and reduce fees.
• Yield Optimization – How publishers maximize revenue using unified auctions and header bidding.
• Advanced concepts (less common) – VAST/VMAP protocols, header bidding wrappers, and real-time data streaming architectures.

Example scenarios:

• "How would you optimize an ad decision engine to handle high-concurrency traffic during a major live-streaming event?"
• "Explain how you would minimize latency in a CTV ad insertion workflow."

Case Study & Strategic Problem Solving

Interviewers use case studies to see how you approach complex, ambiguous problems under pressure. They want to see a structured, logical methodology.

Be ready to go over:

• Problem Deconstruction – Breaking a massive business challenge into smaller, addressable technical hurdles.
• Prioritization Frameworks – Using RICE, MoSCoW, or cost-benefit analysis to justify your roadmap decisions.
• Experimentation Design – Formulating clear hypotheses, defining control groups, and setting success metrics.
• Advanced concepts (less common) – Designing cross-device attribution models using ACR data.

Example scenarios:

• "Walk me through how you would launch a new self-serve advertising platform for mid-market advertisers."
• "How would you design an experiment to test a new ad scoring algorithm without impacting existing revenue?"

Technical Problem Solving & Analytics

You will need to demonstrate that you can work effectively with data scientists and engineers to build data-driven products.

Be ready to go over:

• Data Manipulation – How you use SQL to extract insights from massive datasets.
• API and System Integrations – Understanding how different platforms exchange data securely and efficiently.
• BI & Reporting – Leveraging tools like Tableau, Domo, or Quicksight to build actionable dashboards for stakeholders.

Example scenarios:

• "How would you design a dashboard to monitor the health of our programmatic bidding pipelines?"
• "Describe how you would debug an API integration failure between our ad server and a major DSP."