Senior Staff Marketing Data Scientist, Quizlet

• 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
• Multiparty data fluency in the following:
• MMPs: AppsFlyer (preferred), Adjust, or Branch (SDK events, postbacks, SRNs, SKAN schemas)
• Ad platforms & APIs: Meta/Google/TikTok/Snap/YouTube/DV360/TTD; influencer/affiliate platformsWeb/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
• 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
• As an equal opportunity employer and a tech company committed to societal change, we welcome applicants from all backgrounds. Women, people of color, members of the LGBTQ+ community, individuals with disabilities, and veterans are strongly encouraged to apply. Come join us!

Desirable

• Our Data Science team at Quizlet partners with the Product, Marketing, and Finance teams to define the metrics that matter and to 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, AppsFlyer/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
• 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
• Handle ID fragmentation, 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