Data Analyst: Ranking Team

3+ years analyzing complex experiments and extracting actionable insights from large, noisy datasets. Experience with statistical testing and practical experiment design. Write optimized SQL queries for terabyte-scale data extraction and transformation. Proficiency with distributed systems like Spark for large-scale data processing. Strong skills in exploratory analysis, custom metrics development, and building internal tools using Python. Experience with data science libraries and automation. Understanding of ML pipelines, training data quality, and ranking/recommendation metrics. Familiarity with search relevance and personalization concepts. Design metrics that accurately reflect model and product performance. Ensure alignment between technical metrics and business outcomes. Create compelling dashboards using Tableau, Looker, or custom dashboards in Python. Present complex findings clearly to both technical and executive audiences. Influence product and engineering decisions through data storytelling. Collaborate effectively across teams to drive ML and product improvements. Deep curiosity about user behavior and business impact. Connect algorithm changes to real-world customer outcomes.

Analyze A/B tests across models, configurations, and customer segments to quantify business impact and guide ML development. Investigate training data quality, model performance trends, and feature effectiveness at scale. Investigate how ranking changes affect user behavior and conversion metrics. Uncover usage patterns, anomalies, and opportunities for optimization using SQL, Python, and Spark. Define new metrics to measure search relevance, personalization, and model performance. Ensure metrics align with user experience and business goals through rigorous validation. Create scalable dashboards and reporting tools for product, engineering, and leadership teams. Develop debugging tools to explain ranking decisions and identify performance issues. Partner cross-functionally to design experiments, validate hypotheses, and communicate insights. Influence product roadmap and ML strategy through data storytelling.