About the Role
We are looking for a Data Scientist, Performance Analytics within Engineering to build performance intelligence for our advertising platform.
The role will analyze campaign and platform performance, identify anomalies and opportunities, investigate root causes, and translate data into actions for Engineering, Trading, Product, and Business. This is not primarily a reporting role—the focus is understanding what is happening, why, and what we should do about it.
What You'll Do
- Analyze performance across campaigns, inventory, audiences, bidding, models, and conversions.
- Monitor and investigate CPA, CPC, CTR, VCR, ROAS, spend, delivery, and revenue.
- Proactively detect performance anomalies and optimization opportunities.
- Perform root-cause analysis across models, inventory, identity, attribution, audience, and data quality.
- Design and analyze A/B tests and experiments.
- Build reusable SQL/Python analyses, metrics, and automated diagnostics.
- Partner with Engineering and Trading to turn insights into measurable improvements.
- Convert recurring investigations into AI-assisted troubleshooting and automation.
We'd Love for You to Have
- Strong SQL and Python skills with experience analyzing large-scale datasets.
- Strong analytical, statistical, and experimentation fundamentals.
- Experience with platforms such as Snowflake, Spark, Trino, Databricks, or BigQuery.
- Understanding of data pipelines, data modeling, and data quality.
- Strong problem-solving and communication skills.
- AdTech, marketplace, recommendation, or high-scale platform experience preferred.
- Experience with RTB, bidding, attribution, campaign optimization, or ML-driven systems is a strong plus.
Qualifications:
- Bachelor's degree in Engineering (CS/IT) or an equivalent degree from a well-known institute or university; advanced degree is a plus but not required given depth of experience.
What Success Looks Like
Detect earlier → Diagnose faster → Recommend action → Automate
The goal is not more dashboards. The goal is to create a performance intelligence capability that improves campaign outcomes, reduces investigation time, guides Engineering/Trading decisions, and becomes the foundation for AI-native troubleshooting.
AI-Enabled Engineering Mindset:
We value engineers who actively leverage Generative AI tools and IDEs (e.g. GitHub Copilot, ChatGPT, Claude, Cursor, Windsurf etc.) to accelerate development, improve code quality, automate repetitive tasks, and enhance documentation and debugging workflows. Engineers who demonstrate AI-first thinking using these tools to drive faster experimentation, ideation, and technical execution will thrive in our high-scale, performance-critical environment.
Additional Information:
