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Lead Business Intelligence Analyst

Job Description

Remote position, only for professionals based in Argentina or Uruguay

RYZ Labs is seeking a Lead BI Analyst to join one of our clients’ teams building a robust, scalable analytics foundation to power data-driven decision making. In this role, you will transform complex data from product, monetization, and operational systems into clear, actionable insights that directly impact company strategy.

You will own the design of analytical models, KPI frameworks, and high-impact dashboards used by leadership on a daily basis. Working closely with cross-functional teams—including Product, Engineering, AdOps, Sales, and Operations—you will turn complex data signals into meaningful business recommendations.

The ideal candidate combines strong technical expertise in SQL and modern data platforms with a deep understanding of monetization and user behavior. You will also play a key role in shaping how the BI function scales, establishing best practices, improving data reliability, and mentoring other analysts.

What You’ll Do

Data Modeling & Analysis

  • Build and maintain layered analytical models across device lifecycle, app usage, and monetization (RPH, ARPU, eCPM, fill-rate, retention).

  • Reconcile data from multiple operational, product, and revenue systems; surface and track discrepancies.

  • Create entity-centric models for health, attribution, and longitudinal behavior.

  • Analyze auction funnels end-to-end (requests → bids → wins → impressions → revenue) and diagnose drop-offs.

  • Monitor core KPIs with anomaly detection and investigation playbooks to accelerate root-cause analysis.

  • Develop cohorting, time-series, and survival analyses for growth, churn, and LTV.

  • Implement anomaly detection and alerting on core revenue/usage KPIs.

Dashboarding & Reporting

  • Design scalable KPI dashboards in Apache Superset (daily/weekly/monthly) for executives and operators; enable self-serve exploration.

  • Establish a governed metrics layer/semantic definitions to keep “one source of truth” across teams.

  • Use templating/parameterization to make dashboards reusable by region, app, device class, cohort, etc.

Stakeholder Partnership

  • Act as a thought partner to AdOps, Product & Engineering, Sales, and Operations—turning noisy signals into clear recommendations.

  • Prepare concise, executive-ready narratives (dashboards, memos, Town Hall content) with takeaways and next steps.

Data Engineering Collaboration

  • Align on schemas, SLAs, and data contracts; improve pipeline reliability and query performance.

  • Build performant rollups/aggregate tables (daily/weekly/hourly) and materialized views for high-traffic queries; set sensible refresh cadences.

  • Add tests, documentation, and lineage so models are trustworthy and maintainable.

Project Leadership

  • Drive special studies (e.g., frequency & reach efficiency, identity/household dedupe, geo/DMA lifts, referral and cohort health).

  • Shape analytics roadmap, structure JIRA epics, and mentor analysts in rigorous, iterative workflows.

What We’re Looking For

Core Qualifications

  • 5+ years in BI/Data Analytics (media/CTV/streaming or ad-supported required), owning high-impact dashboards and analyses.

  • Expert SQL on modern warehouses (Redshift/Snowflake/BigQuery); comfortable with multi-CTE patterns, window functions, tuning, and semi-structured JSON/SUPER parsing.

  • Strong BI chops (Superset/Tableau/Looker/Mode) with an eye for clarity, performance, and reuse. We currently use Superset for our visualizations.

  • Fluency in monetization metrics (ARPU, CPM/eCPM, RPH, fill-rate, auction stages) and attribution nuances.

  • Familiarity with streaming/app lifecycle data (sessions, playback, retention, cohorts) and high-volume event streams.

  • Excellent communicator: crisp problem framing, clear data stories, and pragmatic recommendations.

  • Program/project mindset: prioritization, stakeholder alignment, on-time delivery.

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