Growth Intelligence Engineer (Ads & Revenue)

NewsBreak • Mountain View, CA

5d • Hybrid

About The Position

NewsBreak is seeking a curious, technically strong data professional to join our Corporate Ventures and AI Operations team. This hybrid role sits at the intersection of data engineering, data science, and revenue operations. The engineer will build and maintain pipelines for ads data, develop recommendation algorithms, manage commission and quota-setting processes for the ad sales team, and collaborate with business stakeholders to translate data into decisions. The role requires a focus on user experience, aiming to optimize engagement, retention, and monetization through data-driven strategies and system development.

Requirements

• 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

Nice To Haves

• 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

Responsibilities

• 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.
• 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.
• 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.
• 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.
• 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.

Benefits

• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level