Bachelor's degree in a quantitative discipline (Statistics, Economics, Mathematics, Computer Science, Engineering, or related)
1-2 years of experience analyzing large datasets (including internships or relevant projects)
Strong SQL skills for complex queries and database optimization
Experience with Python or R for data analysis and visualization
Understanding of foundational statistics (distributions, correlation vs. causation, hypothesis testing)
Curious and proactive mindset with strong problem-solving abilities
Familiarity with Connected TV (CTV) and digital advertising is a plus
Responsibilities
Analyze campaign delivery and pricing strategies to optimize CTV buying
Conduct exploratory analyses to diagnose campaign performance and inventory quality
Translate auction telemetry and viewing signals into actionable insights
Build analytical workflows and statistical summaries for cross-device evaluation
Collaborate with Data Lead and Machine Learning team to validate hypotheses and measure impact
Benefits
Be part of a leading, innovative company in mobile advertising
Join a motivated and youthful team
Opportunity to travel to Barcelona HQ for collaboration
Comprehensive medical, dental, and vision benefits
Exposure to global app publishers and media partners
Learning and training opportunities for career growth
Full Job Description
About the Role
We are seeking an analytical, detail-driven Data Scientist (CTV Analytics) to join our New York team. In this individual contributor role, you will focus on optimizing how we buy, deliver, and measure performance across Connected TV (CTV) inventory.
You will dig into massive volumes of streaming and programmatic bidstream data, diagnosing performance bottlenecks, testing buying strategies, and providing actionable recommendations to maximize ROAS and campaign scale for our advertising partners. Responsibilities
CTV Strategy Optimization: Analyze campaign delivery, bid shading, floor pricing, and fill rates across streaming platforms and SSPs to optimize buying strategies.
Performance Deep-Dives: Run exploratory analyses and statistical deep-dives to diagnose fluctuations in campaign performance, inventory quality, and ad spend efficiency.
Data-Driven Insights: Translate complex auction telemetry and viewing signals into clear, actionable recommendations for our commercial, programmatic operations, and product teams.
Metric Definition & Reporting: Build reliable, repeatable analytical workflows and ad-hoc statistical summaries to evaluate cross-device reach and frequency.
Cross-Functional Collaboration: Work closely with the US Data Lead and Machine Learning team to validate hypotheses and measure the commercial impact of optimization changes.
Requirements
Bachelor's degree in a quantitative discipline (Statistics, Economics, Mathematics, Computer Science, Engineering, or related).
1-2 years of professional experience analyzing large datasets (internships or relevant analytical projects included).
