Company
Technology
AdsAIAnalyticsLead
Neural analysis suggests this role is
optimal for Lead candidates.
“Ads AI Analytics Lead. Skills: Data Science, Analytics Engineering, AI, ML”
What You'll Achieve.
Measure business impact; Improve model outputs; Improve system performance
Industry & Context.
Translate business challenges
What They're Looking For.
Must Have
3–6 years analytics engineering, 3–6 years data science, 3–6 years applied AI, 2+ years advertising data, 2+ years retail media data, 2+ years e-commerce data, SQL proficiency, Python proficiency, Dbt experience, Snowflake experience, BigQuery experience, Data modeling understanding, Testing frameworks understanding, Data contract principles understanding, Data pipelines orchestration experience, Advertising performance metrics understanding, A/B tests experience, Uplift models experience, Experimentation frameworks experience, ML concepts understanding, Evaluation frameworks experience, Guardrails experience, Human-in-the-loop validation experience, Ability to operate in fast-paced environments, Ability to deliver production-grade systems
Nice to Have
Workflow automation tools familiarity, Modern AI/ML product development practices familiarity
How You'll Work.
Team & Collaboration
Engineering teams; Product teams
Communication Scope
Deliver insights
Full Job Description
## Accountabilities Define and maintain Ads ontologies and semantic frameworks covering campaigns, budgets, bids, creatives, audiences, and placements. Build and optimize dbt models and curated data marts in Snowflake with robust data contracts, testing, and quality standards. Design and implement data pipelines for structured and unstructured Ads data using modern orchestration and transformation tools. Develop retrieval-augmented generation (RAG) workflows for Ads intelligence, including hybrid search, ranking, and evaluation systems. Create agent reasoning frameworks, tool definitions, and policy guardrails for AI-driven Ads decision-making systems. Design and execute experimentation frameworks, including A/B tests and uplift analyses to measure business impact. Establish evaluation metrics for AI systems, including precision, recall, latency, calibration, hallucination rate, and cost efficiency. Translate advertising business challenges into measurable agent behaviors and performance KPIs such as ROAS, CPA, CTR, CVR, pacing, and incrementality. Build dashboards and reporting layers to communicate insights using visualization tools and analytics platforms. Collaborate with engineering and product teams to ship scalable, production-ready AI and analytics systems. Continuously improve model outputs and system performance through iterative experimentation and feedback loops. Requirements 3–6 years of experience in analytics engineering, data science, or applied AI roles. 2+ years of experience working with advertising, retail media, or e-commerce data domains. Strong proficiency in SQL and Python, with hands-on experience in dbt and Snowflake or BigQuery. Deep understanding of data modeling, testing frameworks, and data contract principles. Experience building and orchestrating data pipelines using tools such as dbt and Airflow. Familiarity with data visualization tools such as Looker, Tableau, Power BI, or equivalent platforms. Solid understanding of advertising pe
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