Minted is looking to optimize acquisition, retention, and incremental revenue by turning multichannel data into clear insights, partnering with channel leads and product/engineering to improve attribution, forecast impact, and guide budget decisions.
Requirements
- Strong SQL: Complex queries, large tables (millions of rows), performance optimization
- Proficient in BI tools and comfortable with GitLab/GitHub workflows
- Familiarity with attribution models, channel performance, and digital marketing metrics
- Python experience for data manipulation, AI (Agentic, MCP, etc) exposure/experience, Predictive modelling / ML exposure, Data pipeline/semantic layers (DBT, Dagster, Prefect, Kestra, etc.)
- Snowflake, Looker, Hex, GitLab, Airflow, AI agent (co-pilot, etc)
Responsibilities
- Maintain and evolve our marketing attribution model (FA model).
- Reconcile platform-reported metrics with internal data.
- Support incrementality testing and channel performance analysis
- Translate ambiguous business asks into technical requirements; deliver clear, actionable insights on site traffic, return on ad spend ROAS, customer LTV, and channel contribution
- Collaborate with Marketing channel leads, Product, and Engineering to instrument tracking, close data gaps, and improve measurement infrastructure.
- Write production-quality SQL against large datasets (Snowflake); build and maintain Looker explores and conduct ad hoc analyses; contribute to GitLab-based analytics workflows.
Other
- 3+ years in an analytics role focused on marketing or growth (e-commerce/marketplace preferred) analytics
- Translate technical findings for non-technical audiences; work effectively across functions
- The role is hybrid and based out of our San Francisco office.
