Growth Intelligence Engineer (Ads & Revenue)
Role details
Job location
Tech stack
Job description
We're looking for a curious, technically strong data professional to join our Corporate Ventures and AI Operations team. This is a hybrid role sitting at the intersection of data engineering, data science, and revenue operations - you'll build and maintain the pipelines that power our ads data, develop recommendation algorithms that keep users coming back, own commission and quota-setting processes for our ad sales team, and work closely with business stakeholders to translate data into decisions. You care about the milliseconds between a user opening the app and finding something they love. You think about what makes someone stay, subscribe, and come back tomorrow - and you build the systems that make that happen at scale., Audience Retention & Performance
- Instrument and monitor performance signals (load times, stream quality, error rates) to ensure users experience fast, flawless products across web, app, and live streams
- Build and maintain dashboards that track engagement and retention metrics - session length, scroll depth, return rate, and drop-off points
- Identify friction in the user journey through data and partner with product and engineering to eliminate it
- Design and analyze experiments that test retention-boosting product changes
Data-Driven Personalization
- Build and iterate on recommendation algorithms that surface the right content to the right user at the right moment
- Develop the data infrastructure (feature pipelines, training datasets, feedback loops) that keeps recommendation models fresh and accurate
- Measure the impact of personalization on session time, click-through rates, and long-term retention through rigorous experimentation
- Partner with the content and product teams to translate algorithmic output into intuitive user experiences
Data Engineering
- Build, maintain, and improve data pipelines that process large-scale ads, user event, and engagement data
- Write clean, well-tested SQL and Python/PySpark code to transform raw data into reliable, analysis-ready datasets
- Oversee the data architecture supporting ad-tech integrations, paywall flows, and subscription checkout - ensuring these monetization surfaces are instrumented, reliable, and fast
- Monitor data quality and proactively surface and resolve data integrity issues
- Partner with platform and engineering teams to ensure pipelines are scalable and well-documented
Data Science & Analytics
- Design and analyze A/B experiments to measure the impact of ads, growth, and personalization initiatives
- Build predictive models (e.g., propensity, churn, re-engagement) to improve targeting and campaign performance
- Develop dashboards and reports that give the business clear visibility into key metrics
- Translate ambiguous business questions into structured analytical frameworks
Revenue Operations & Sales Strategy
- Own the end-to-end commission calculation process for the ad sales team - ensuring accuracy, timeliness, and clear documentation
- Partner with Sales and Finance to design and model sales quotas, incorporating historical performance data, market benchmarks, and business targets
- Build and maintain models to simulate commission payout scenarios and evaluate the cost and incentive impact of quota and comp plan changes
- Work with cross-functional partners (product, marketing, sales) to understand their data needs and deliver actionable insights
- Proactively identify trends and anomalies in ads performance and communicate them clearly to stakeholders
- Support operational reporting and help automate recurring analyses to free up team bandwidth
Requirements
Do you have experience in SQL?, Do you have a Bachelor's degree?, * Bachelor's or Master's degree in a quantitative field (Statistics, Computer Science, Economics, Mathematics, Engineering, or similar)
- Strong SQL skills; comfort writing complex queries across large datasets
- Experience with Python for data analysis (pandas, numpy, scikit-learn, etc.)
- Familiarity with distributed data processing tools (Spark, Hive, or similar)
- Understanding of A/B testing and experimental design principles
- Ability to communicate data findings clearly to both technical and non-technical audiences, * Exposure to ads data, growth metrics, or attribution frameworks
- Experience with recommendation systems, collaborative filtering, or content ranking
- Familiarity with ad-tech concepts: ad serving, DSPs, SSPs, header bidding, or paywall/subscription systems
- Familiarity with cloud data platforms (Databricks, BigQuery, Snowflake, or similar)
- Experience building ML models in a production or near-production context
- Prior internship or work experience at a tech, media, or consumer company
Benefits & conditions
Pulled from the full job description
- Health insurance
- 401(k) matching
- Paid time off
- Vision insurance
- Health savings account
- Dental insurance
- Flexible spending account, We offer a competitive benefits package:
- Health, dental, and vision care for you and your family (100% coverage for employee)
- Top-tier 401(K) plan with company matching
- Paid time off and paid holidays
- FSA, HSA and commuter benefits programs
- Team activity budget