Product Data Analyst
Posted Updated
Description
- 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 Data 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 turn data into decisions. You’ll translate open-ended questions from the team into clear insights, dig into why campaigns or models underperform and own the A/B testing process end to end, from design to interpretation
- You’ll build the dashboards and reporting frameworks that keep the team’s main KPIs visible and actionable, and act as the main driver behind data-backed decision-making across the squad
- It’s a technical role at its core, but your real value is in bridging the gap between the engineering/ML side and the business side — making sure what’s being built actually translates into impact
- Design and evaluate 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’s 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
- 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 experience
- Solid grasp of A/B testing and experimentation fundamentals (significance, sample size, basic causal inference)
- Strong SQL experience, comfortable with complex queries against large datasets
- Comfortable working with high-volume, high-cardinality data
- Working proficiency in Python (pandas, numby, statsmodel/scipy libraries)
- Experience with cloud data warehouses (BigQuery preferred; Snowflake/AWS also valuable)
- 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 welcome
- Good communication skills in both English & Spanish
- Experience with BI tools — Looker, PowerBI and/or Tableau
- Experience in programmatic advertising, ad-tech, or mobile marketing specifically
- Exposure to predictive modeling or basic ML (churn prediction, forecasting, segmentation)