Ads AI Analytics Lead
New
Based in the United StatesFull-TimeLead
Salary131,000 - 165,000 USD per year
Apply NowOpens the employer's application page
Job Details
- Experience
- 3–6 years
- Required Skills
- PythonSQLMachine LearningSnowflakeTableauAirflowBigQuerydbtLooker
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 performance metrics including ROAS, CPA, CTR, CVR, LTV, and auction dynamics.
- Experience designing and running A/B tests, uplift models, or other experimentation frameworks.
- Understanding of machine learning concepts applied to recommendations, forecasting, or optimization problems.
- Strong communication skills with a proven ability to deliver insights that influence business decisions.
- Experience working with evaluation frameworks, guardrails, and human-in-the-loop validation systems.
- Ability to operate in fast-paced, cross-functional environments and deliver production-grade data or AI systems.
Responsibilities
- 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.
View Full Description & ApplyYou'll be redirected to the employer's site
