Sr. Marketing Data Scientist

About Quizlet

At Quizlet, our mission is to help every learner achieve their outcomes in the most effective and delightful way. Our $1B+ learning platform serves tens of millions of students every month, including two-thirds of U.S. high schoolers and half of U.S. college students, powering over 2 billion learning interactions monthly. We blend cognitive science with machine learning to personalize and enhance the learning experience for students, professionals, and lifelong learners alike.

We’re energized by the potential to power more learners through multiple approaches and various tools. Let’s build the future of learning.

Our Data Science team at Quizlet partners with the Product, Marketing, and Finance teams to define the metrics that matter and turn noisy signals into clear, causal decisions. This role builds and operates the TOF measurement system that informs spend, audiences, creative, and channel mix.

You’ll design trusted incrementality and MMM measurement, stitch multiparty data (ad platforms, Apps Flyer/MMP, web/app analytics, internal events), and turn models into concrete budget and targeting decisions. You will not manage people; you’ll lead through technical depth and repeatable delivery. This is an onsite position in our San Francisco office; employees are required to be in the office at least three days per week.

• 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, You Tube, Tik Tok, Snap, DV360/TTD, affiliate/influencer), MMP data (Apps Flyer/Adjust/Branch), GA4/GTM, and internal product/financial events.
• Handle , SKAN/ATT, cookie loss, missingness, and deduplication; document assumptions and data quality SLAs.
• Ship decision‑driving reporting: build exec‑ready views (e.g., brand search, share of voice, qualified‑visit rate, creative learning) tied to sign‑ups, retention, and LTV.
• Run source‑health monitoring with forward projections and risk flags.
• Evaluate and manage MMM vendors, GTM/analytics implementers, survey/brand trackers, CDPs, and clean‑room partners; write SOWs, define success metrics, and QA their models/tags.
• Make buy‑vs‑build recommendations and own integrations end to end.

• 7–10+ years in marketing analytics/data science (consumer or subscription businesses), with recent hands‑on TOF growth work.
• 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:
  Apps Flyer (preferred), Adjust, or Branch (SDK events, postbacks, SRNs, SKAN schemas).
• Ad platforms & APIs:
  Meta, Google, Tik Tok, Snap, You Tube, 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/Num Py; PyMC/Stan a plus), Big Query/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.
• Communication with crisp narratives that move spend and targeting decisions; comfortable presenting to…