Quizlet is looking to design and deliver AI-powered learning tools that scale across the world and unlock human potential. The Data Science team partners with Product, Marketing, and Finance to define metrics, turn noisy signals into clear, causal decisions, and build/operate a TOF measurement system that informs spend, audiences, creative, and channel mix.
Requirements
- You’ve designed, powered, run, and interpreted geo holdouts, heavy-ups, synthetic control; you know pitfalls (seasonality, contamination, spillovers) and how to validate assumptions
- Built or owned an MMM (or ran a vendor) including spec/priors/regularization, calibration to experiments, and turning results into allocation decisions
- MMPs: AppsFlyer (preferred), Adjust, or Branch (SDK events, postbacks, SRNs, SKAN schemas)
- Ad platforms & APIs: Meta/Google/TikTok/Snap/YouTube/DV360/TTD; influencer/affiliate platforms
- Web/App analytics & tagging:GA4, GTM (incl. server-side), consent/attribution config; event/identity standards across web/app.
- Data engineering literacy: SQL (advanced), Python or R (pandas/NumPy; PyMC/Stan a plus), BigQuery/Snowflake/Redshift, dbt; basic orchestration (Airflow/Dagster) and CI hygiene
- Experimentation rigor in power/sizing, CUPED, pre-trend checks, non-compliance handling, synthesis across tests; can teach others
Responsibilities
- Own cross-channel incrementality: stand up and analyze geo/user holdouts, heavy-ups, synthetic controls, CUPED/diff-in-diff, and brand-lift; produce incremental qualified visits / sign-ups with uncertainty
- Build an always-on testing calendar and power analyses; automate ingestion and readouts
- Triangulate MMM + experiments + platform signals
- Operate or co-own an MMM (in-house or vendor) and calibrate to holdouts; define decision rules (MMM for budgeting, experiments for validation, platform MTA for ops)
- Produce response curves and marginal dollar recommendations by channel/geo/audience; model payback windows (30-day to multi-year LTV) and saturation guardrails
- Wrangle multiparty data (imperfect by default)
- Join ad platform exports/APIs (Meta, Google, YouTube, TikTok, Snap, DV360/TTD, affiliate/influencer), MMP data (AppsFlyer/Adjust/Branch), GA4/GTM, and internal product/financial events
Other
- This is an onsite position in our San Francisco office.
- Employees are required to be in the office a minimum of three days per week: Monday, Wednesday, and Thursday and as needed by your manager or the company.
- You will not manage people; you’ll lead through technical depth and repeatable delivery.
- Communication with crisp narratives that move spend and targeting decisions; comfortable presenting to Directors/VPs
- Vendor leadership with selection, SOWs, success criteria, and hold-vendors-accountable modeling/tagging reviews
