Data Analyst
The Intelligence Architect
Executive Mission & The Big Picture
The Data Analyst is the intelligence layer behind every optimization decision at Open G Scale. This role transforms raw campaign, auction, and platform data into actionable insights that drive revenue, reduce waste, and accelerate growth across all operations.
In the AdTech world, the Data Analyst is the "Truth Finder." They dig through billions of bid requests, impression logs, and conversion events to surface the patterns that humans cannot see. Their "Big Picture" is Data-Driven Decision Making: ensuring that every dollar spent, every bid placed, and every optimization made is backed by rigorous analysis rather than gut feeling. They are the foundation upon which scalable, profitable advertising operations are built.
Core Strategic Objectives
Build and maintain reporting dashboards across campaigns, platforms, and revenue streams that serve as the single source of truth for the entire organization.
Analyze bid-level data, auction logs, and fill rates to identify inefficiencies and hidden revenue opportunities that would otherwise go unnoticed.
Create automated alerts and anomaly detection systems for campaign performance drops, ensuring problems are caught in minutes, not days.
Support Media Buyers and Traffickers with data-driven optimization recommendations that directly impact ROAS and margin.
Develop attribution models and revenue forecasting frameworks that enable strategic planning and resource allocation.
Perform competitive analysis using public data sources and industry benchmarks to position the organization ahead of market shifts.
Daily Operations & Core Responsibilities
Dashboard Monitoring & Health Checks
Starting every day with a sweep of all active dashboards to identify anomalies, delivery issues, or unexpected performance shifts across campaigns and platforms.
Data Extraction & ETL Pipeline Management
Pulling data from ad servers, DSPs, SSPs, and analytics platforms. Cleaning, transforming, and loading it into centralized databases for analysis.
Ad Hoc Analysis Requests
Responding to urgent questions from Media Buyers, Account Managers, and leadership. Why did CPMs spike yesterday? Which segments are underperforming?
Report Generation & Distribution
Building weekly and monthly performance reports with clear visualizations, annotations, and actionable recommendations for different stakeholder audiences.
Anomaly Investigation
When automated alerts fire, the Data Analyst investigates root causes: bot traffic, bid landscape shifts, creative fatigue, inventory quality changes, or technical misconfigurations.
Model Refinement
Continuously improving forecasting models, attribution logic, and scoring algorithms based on new data and changing market conditions.
Cross-Team Data Consultations
Sitting with Buyers, Traffickers, and Account Managers to walk through data findings and translate complex statistical insights into plain-language action items.
The Collaboration Ecosystem
Internal Collaboration
With Media Buyers
Providing the analytical backbone for optimization decisions. The Analyst surfaces which audiences, placements, and bidding strategies are delivering the best returns.
With Media Traffickers
Validating that campaigns are delivering correctly by cross-referencing trafficking setups with actual impression and click data.
With Account Managers
Translating raw data into client-ready insights. The Analyst prepares the data layer that the AM transforms into the strategic narrative.
With AdTech Developers
Collaborating on data infrastructure, API integrations, and custom reporting tools. The Analyst defines the data requirements; the Developer builds the pipeline.
External Collaboration
With Platform Data Teams
Working with DSP, SSP, and ad server support teams to resolve data discrepancies, access new reporting APIs, and understand platform-specific metrics.
With Verification Partners
Coordinating with IAS, DoubleVerify, and MOAT to integrate brand safety and viewability data into unified reporting frameworks.
With Industry Data Providers
Leveraging third-party data sources like Pathmatics, SimilarWeb, and Sensor Tower for competitive intelligence and market benchmarking.
Tech Stack & Tools
Data Querying & Processing
Visualization & Reporting
AdTech Data Sources
Analytics & Attribution
KPIs & Success Metrics
Dashboard Accuracy & Adoption Rate
Percentage of dashboards that are error-free and actively used by their intended audience.
A dashboard nobody uses is a wasted investment. Accuracy builds trust; adoption proves relevance.
Time-to-Insight
How quickly anomalies are detected, investigated, and reported with actionable recommendations.
In programmatic advertising, every hour of undetected underperformance costs real money.
Revenue Impact of Recommendations
Measurable revenue increase or cost reduction attributable to data-driven recommendations.
Proof that analysis translates into business value, not just interesting charts.
Forecast Accuracy
How closely revenue projections match actual results over 30, 60, and 90-day windows.
Accurate forecasting enables strategic resource allocation and prevents budget surprises.
Automation Rate
Percentage of repetitive reporting tasks automated through scripts or pipeline tools.
Automation frees analyst time for high-value strategic work.
Native Dictionary
The Learning Curve
The Data Explorer
Months 1-3Concepts: Understanding the AdTech data ecosystem: what data lives where, how platforms report, and why numbers never perfectly match.
Skills: SQL queries against ad server databases, basic Looker Studio dashboards, company data dictionary.
Milestone: Building a weekly campaign performance dashboard actively used by the Media Buyer team.
The Insight Generator
Months 3-6Concepts: Moving beyond what happened to why it happened. Auction dynamics, seasonality, supply-demand relationships.
Skills: Automated anomaly detection, advanced SQL, Python scripting, presenting to non-technical stakeholders.
Milestone: Identifying a hidden revenue leak that delivers measurable financial impact once fixed.
The Strategic Analyst
Months 6-12Concepts: Forecasting, attribution modeling, competitive intelligence. Connecting data strategy to business strategy.
Skills: Predictive models, A/B testing frameworks, 70%+ report automation, mentoring junior analysts.
Milestone: Quarterly strategic analysis that influences leadership decisions on budget and market expansion.
The Intelligence Architect
12+ MonthsConcepts: Designing the entire data strategy: what to measure, how, and building a data-driven culture.
Skills: Data infrastructure design, cross-functional leadership, advanced statistical modeling.
Milestone: Self-service analytics platform empowering every team member to access data independently.