- Data and how it is used play a central role at Jampp and are at the heart of our product, business, operational, and financial decisions. We're building a new deep learning platform based on shared embeddings - moving from hand-crafted model features to representations our models learn directly from raw data, shared across prediction, bidding, and pricing
- As Product BI Analyst, you'll join this initiative from day one, working shoulder-to-shoulder with our Data Science and ML teams as the analytical bridge between the models and the business
- Your job is to understand the data, monitor experiments, and bring back the angle the model can't: which advertisers benefit most from a new model, where we're underperforming and why, what patterns the numbers reveal that a purely technical view might miss. It's a highly technical role by BI standards - you'll be deep in auction-level, high-cardinality data every day - but the value you add is business judgment, not model architecture
- Monitor ongoing A/B tests across models and campaigns, going beyond "did it win or lose" into why, and for which advertisers or segments
- Deep-dive into auction-level and campaign data - large volumes, high cardinality (millions of apps, placements, creatives) - to surface patterns the team hasn't already been looking for
- Build and maintain dashboards and reporting frameworks (Looker/Tableau) that give the team clear, actionable visibility into performance
- Translate technical model changes into business impact: what it means for CPI, CPA, and ROAS,



and where there is an opportunity to push for more advertiser budget
- Bring proactive ideas to the table. We're not looking for passive reporting - we want insight, brainstorming, and pushback
- Work with automated pipelines (SQL, Python) to keep monitoring and reporting scalable as the team and initiative grow
- Partner closely with Data Scientists and ML Engineers: understand what's being built, flag data quality issues, and validate results from a business lens

Solid grasp of A/B testing and experimentation fundamentals (significance, sample size, basic causal inference)4-8 years of experience in Data Analytics, BI, Marketing Analytics, or Growth Analytics. xhfqzwm We value motivation and analytical sharpness as much as years of experienceExperience with cloud data warehouses (BigQuery preferred;
Snowflake/AWS also valuable)Strong SQL (comfortable with complex queries against large datasets) and working proficiency in Python (pandas-level analysis, not software engineering)Understanding of how a DSP/ad-tech ecosystem works - auctions, impressions, SSPs, MMPs. Background in a DSP, SSP, ad exchange, or mediation platform is equally welcomeGood communication skills in both English & SpanishComfortable working with high-volume, high-cardinality dataExperience with BI tools - Looker and/or TableauExposure to predictive modeling or basic ML (churn prediction, forecasting, segmentation)Experience in programmatic advertising, ad-tech, or mobile marketing specifically

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📌 Product Business Intelligence Analyst (Madrid)
🏢 Jampp
📍 Madrid