Ads AI Analytics Lead II

• Define Ads ontologies and canonical metrics across campaigns, budgets, bids, creatives, audiences, and placements to power consistent reasoning and recommendations.

• Build robust dbt models and curated marts in Snowflake (or BigQuery) with clear data contracts, tests, SLOs, and monitoring; orchestrate pipelines with Airflow.

• Ingest, structure, and enrich unstructured Ads content; publish retrieval-ready datasets leveraging managed search/vector services to enable high-quality grounding.

• Design and evaluate RAG workflows (hybrid search, re-ranking) with explicit quality and latency targets; iterate via offline/online experiments to improve performance.

• Design agent reasoning, tools, and policies for Ads use cases, including human-in-the-loop approvals and guardrails that balance safety, cost, and speed.

• Establish evaluation suites and dashboards tracking precision/recall, calibration, hallucination rate, latency, and cost; drive continuous model and system improvements.

• Run A/B and uplift experiments to quantify business impact; own KPIs such as ROAS lift, pacing accuracy, RCA precision/recall, forecast MAPE, and time-to-insight.

• Partner with Ads Product, Ads Engineering, Sales leadership, Data Engineering, and R&D to align roadmaps, de-risk launches, and ship high-quality production agents.

• Own your workstream end to end—from data and pipelines to the UI and agent logic—delivering secure, observable, and reliable tooling that’s adopted by the field.

• 4–7 years of experience in analytics engineering, data science, or applied AI, with advanced proficiency in Python and SQL.

• 2+ years working with ads, retail, or e‑commerce data.

• Hands-on experience with dbt and Snowflake or BigQuery, including data modeling, testing, documentation, and managing data contracts.

• Experience orchestrating data pipelines with Airflow (or a similar scheduler), including alerting and on-call support for data SLOs.

• Ability to design and run offline/online evaluations and A/B or uplift tests; familiarity with experiment design and statistical inference.

• Fluency in Ads analytics concepts: ROAS, CPA, CTR, CVR, LTV, pacing, auction dynamics, and incrementality.

• Shipped at least one production data or AI system used by business stakeholders, with demonstrable business impact.

• Experience with evaluation and guardrail frameworks and human‑in‑the‑loop QA workflows.

• Proficiency with at least one BI/visualization tool (e.g., Looker, Tableau, Mode, or Power BI).

• Bachelor’s degree in a quantitative field (e.g., Computer Science, Engineering, Statistics) or equivalent practical experience.

• Experience building AI-driven products or agents end to end, including retrieval design (hybrid search, re-ranking) and vector search.

• Deep expertise in advertising products and operations, with a track record of driving automation that improved ROAS, pacing, or operational efficiency.

• Applied experience with Ads modeling techniques such as forecasting, anomaly detection, uplift modeling, and causal inference.

• Hands-on experience with workflow automation or internal tooling (e.g., Retool, Superblocks, Zapier, n8n, Gumloop) and/or front-end frameworks (e.g., React) to translate insights into actions.

• Familiarity with retail media and ad ecosystems (e.g., Amazon Ads, Google Ads, Meta, Shopify, DoorDash) and their measurement frameworks.

Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here. Currently, we are only hiring in the following provinces: Ontario, Alberta, British Columbia, and Nova Scotia.

Offers may vary based on many factors, such as candidate experience and skills required for the role. Additionally, this role is eligible for a new hire equity grant as well as annual refresh grants. Please read more about our benefits offerings here.

For Canadian based candidates, the base pay ranges for a successful candidate are listed below.

CAN

$140,000—$148,000 CAD

Originally posted on Himalayas