We are looking for a sharp, data-driven Senior Product Analyst to join our Tel Aviv team. You will be the analytical backbone of our monetization optimization efforts, focusing on high-velocity testing and monetization strategies. You will support analytics related to product experiments. In this role, you will not only report on results but dive deep into why specific changes occurred, bridging the gap between raw data and product strategy. You will work closely with our Data Science, Product, and Dev teams to ensure data-driven decision-making in a fast-paced environment.
What Youll Do:
A/B Testing & Statistical Analysis
Analyze multiple test results simultaneously, applying rigorous statistical methodologies to validate findings.
Critically evaluate experimental setups to identify and raise flags regarding incorrect test designs or sample biases before they impact decision-making.
Support a high-paced testing environment by providing quick, accurate results and insights to support ongoing optimization efforts.
Deep-Dive Analytics & Insights
Run in-depth deep-dive analyses aimed at explaining why a certain change brought (or didn't bring) the desired result, rather than just reporting the outcome.
Translate complex data outcomes into actionable recommendations that help the team formulate new hypotheses for future tests.
Present findings on user insights to stakeholders, recommending concrete next steps to inform content and product decisions.
Model Evaluation & Collaboration
Work intimately with Data Scientists to evaluate machine learning model performance.
Determine if new models perform better or worse than previous iterations and provide granular feedback to the broader team.
Advocate for new data collection or feature engineering that would improve model accuracy or analysis capabilities.
Requirements: 5+ years of experience in a data analysis or product analyst role, with a strong focus on A/B testing, optimization, or product analytics.
Advanced SQL skills - able to query and manipulate large datasets in a cloud data warehouse environment.
Statistical Expertise: Solid understanding of experimental design in a product context, including sample size calculation, selecting success metrics, and determining statistical significance. You must be able to spot flaws in test design.
Analytical Depth: Strong problem-solving skills with the ability to validate data integrity and conduct root-cause analysis to explain user behavior.
Data Modeling: Solid understanding of data modeling and ETL processes. You can design efficient data tables/views for analysis and are familiar with tools like Rivery or other ETL pipelines to help structure data.
Visualization: Experience with data visualization and BI reporting (especially tools like Looker Studio) to create dashboards that track KPIs over time.
Communication: Excellent communication skills, with the ability to explain complex analytical findings in simple terms to non-technical audiences.
Adaptability: Comfortable working in a dynamic startup environment, with the ability to adapt quickly to changing priorities, projects, and business needs.
B.Sc/B.A. in Statistics, Economics, Business, Computer Science, or a related field.
Advantageous:
AdTech & Monetization Context: Knowledge and experience with the AdTech context and the complex logic behind web monetization.
Python Proficiency: Programming skills in Python for executing quick, repetitive analyses and automating analytical workflows.
Advanced Modeling Implementation: The knowledge to run advanced data analysis or to implement custom predictive models beyond basic SQL, utilizing existing libraries and/or tools developed by the internal Data Science team.
This position is open to all candidates.