Applied Scientist II – Ad Systems Optimization

Job Description

Applied Scientist II – Moloco Commerce Media | Confidential Employer

The Tone:
This is a full-time role at Moloco. Moloco develops powerful AI advertising solutions, aiming to make advanced AI accessible beyond large tech companies. This role is vital for improving the performance, efficiency, and reliability of Moloco Commerce Media’s marketplace advertising systems. The Applied Scientist II will contribute directly to enhancing advertiser outcomes, retailer monetization, and overall system stability.

The TL;DR
• Role: Full Time
• Type: Full-time
• Location: In-person, South Korea, South Korea (Seoul) – Seoul

• Team: Applied Science team in MCM; works with software engineers, machine learning engineers, data scientists, and product partners.
• Mission: Improve the performance, efficiency, and reliability of Moloco Commerce Media’s marketplace advertising systems.
• Tech Stack: Python, SQL

What You’ll Actually Do
• Evaluate Systems: Work with other applied scientists, software engineers, and data scientists to evaluate the health, efficiency, and performance of MCM’s core marketplace advertising systems.
• Conduct Analysis: Conduct deep, unbiased analyses on large-scale data to identify inefficiencies, explain performance changes, and uncover root causes across system, model, data, and market changes.
• Design Algorithms: Design, implement, and evaluate algorithms, metrics, and analytical frameworks that improve bidding, pacing, pricing, ranking, and experimentation outcomes.
• Support Launches: Support the launch and ramp of new features by defining success metrics, guiding A/B tests, interpreting results, and making data-driven recommendations.
• Collaborate Effectively: Collaborate closely with Product, Engineering, ML, Data Science, and business stakeholders to translate ambiguous commerce media problems into clear analytical plans and practical solutions.

The Must-Haves
• Background: MS or Ph.D. degree in Computer Science, Statistics, Mathematics, Economics, Operations Research, or a related quantitative field.
• Experience: 4+ years of industry or postgraduate experience in applied science, data science, machine learning, experimentation, optimization, or a related analytical field.
• Skills: Strong foundation in statistics, probability, experimentation, causal reasoning, and optimization; Proficiency in Python and SQL for large-scale data analysis; Ability to analyze complex multi-causal systems, generate hypotheses, evaluate trade-offs, and communicate clear recommendations; Proficient verbal and written English communication skills; Quick understanding of new information and demonstrated ability to learn technical concepts across engineering, machine learning, and data science.
• Bonus: Track record of building positive relationships with collaborators and stakeholders and working effectively with cross-functional partners in a global company.