Campaign Strategist

Campaign StrategistOur client is looking to hire a Campaign Strategist to be the analytical engine behind high-performing campaigns. The Campaign Strategist translates massive datasets into clear decisions, pilot new DL/LLM features, and partners with Client Success, Data Science, and Ad Ops to deliver results across display, OLV, CTV, and emerging channels. This work will improve both client outcomes and our product roadmap.Responsibilities:Monitor pacing, delivery, and performance daily; own QA (pixels/tags, model params, supply lists), discrepancy resolution, and change logsEstablish optimization plans that map to client business metrics (CPA/ROAS/LTV, not just media KPIs)Diagnose bidding behavior and auction dynamics using SQL (and Python when needed) across billions of log rows; separate signal from noiseDesign/run tests (A/B, multi-cell, geo-holdout); publish succinct read-outs with recommendations and next stepsBuild dashboards/scorecards (Tableau/Looker/Sheets) that make complex data legible to technical and non-technical partnersPilot deep-learning optimizers (e.g., CTR/VCR/CPA models, pacing/autotuner) and LLM workflows (brief ?

topics ? inclusion lists; rationale summaries)Document field results and translate into product requirements (signals, guardrails, eval metrics) with Data Science & ProductHelp build the campaign operating system: RACI, runbooks, QA checklists, alerting (pacing/spend anomalies, model drift), experiment registry, reporting standardsIdentify automation opportunities; partner with Eng/Ops to ship scripts/tools that improve speed, accuracy, and repeatabilityCommunicate insights clearly to CS, Ad Ops, and DS; contribute to client-facing performance narratives and QBRs with actionable recommendationsRequirements:BS/BA in a quantitative field3-5 years experience in analytics roles, preferably within AdTech or programmatic media environmentsAdvanced proficiency with SQL, including complex queries, optimization, and joinsStrong analytical skills and comfort with interpreting large-scale data sets (billions/trillions of rows)Demonstrated ability to communicate complex analytical insights effectively to technical and non-technical audiencesSolid understanding of statistical methods and experimentation frameworksExperience with visualization tools like Tableau and proficiency in creating data pipelinesProficiency in Python or similar scripting languagesFamiliarity with predictive analytics, machine learning, and experimentation methodologiesExperience with distributed SQL technologies and handling large-scale log dataKnowledge of online marketing analytics and DSP bidding algorithmsAdvanced degree in analytics, statistics, data science, or related technical field