- 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. 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