Marketing Data Scientist

Job description

**🎨 About OpenArt** OpenArt is an AI Storytelling and Visual Creation Platform used by millions worldwide. We’re building the next generation of creative tools powered by cutting-edge AI, enabling anyone to create videos, visuals, characters, and stories with unprecedented speed and imagination. We believe the future of creativity is AI-native, and we’re shaping that future. **🚀 Why Join OpenArt** - **Ride an inflection point.** OpenArt has grown **7–10X in revenue over the past 2 years** in one of the hottest categories in tech (AI-native creative tools). You're joining while the trajectory is still steep and every measurement decision compounds. - **Own the data science practice behind one of OpenArt's biggest growth levers** — marketing spend across influencer, paid, and lifecycle. - Work across marketing, growth, product, data engineering, and finance — one of the most cross-functional roles in the company. - **Build from 0 → 1.** The attribution model, channel taxonomy, and measurement stack are being laid down right now; you'll help finish the build and then run it. - High ownership, low process, fast iteration environment. **🎯 About the Role** We're looking for a **Marketing Data Scientist** to be our first dedicated marketing DS, partnering with our Head of Data to build measurement, experimentation, and insights for OpenArt's marketing org — across performance marketing, influencer/UGC, and lifecycle/email. You don't need to be an expert in every corner of marketing science. What we care about is that you're **strong in the fundamentals** (SQL, Python, experimentation, at least one measurement specialty), **have real product and business intuition**, and are **hungry to grow into the harder pieces** — with a Head of Data who's done all of it available to teach you. You'll inherit and extend work already in flight — our multi-model attribution build, the Marketing Attribution Alignment with the marketing team, and live incrementality tests (Google brand vs non-brand, Director email upsell holdout). You'll also lead areas we haven't been able to cover well yet, most notably real-time influencer/UGC measurement — currently a big gap and a top priority. **🛠 What You’ll Do** ### Marketing measurement & reviews (weekly rhythm) - Own the weekly review with the influencer marketing team — bring the data, the read, and the recommendation. - Build and maintain **real-time dashboards** for influencer/UGC traffic spikes, CAC / ROAS / payback across channels, and campaign-level performance. - Debug attribution gaps across ad platforms, warehouse, and CRM (Meta Attribution Gap, Impact Radius, Google Ads conversion tracking are all live workstreams). ### Experimentation & insights - Design and run **incrementality tests, holdout tests, and A/B tests** across marketing programs (email, paid channels, influencer where feasible). - Partner on HDYHAU survey design and analysis to correct platform-reported CAC. - Do the deep-dive analyses that shape spend decisions — creative reads, cohort/LTV analysis, channel efficiency, campaign post-mortems. - Work on the marketing attribution build — channel/subchannel/partner taxonomy, attribution windows, priority chain, promo code handling, multi-model attribution. - Contribute to per-creator influencer attribution instrumentation (unique codes / UTMs / landing pages). - Grow into ownership of these areas over time as you build depth. ### Communication - Translate insights into crisp, opinionated recommendations that marketing leaders actually use — written and verbal. - Set the bar for experimentation rigor and marketing measurement quality at OpenArt. **🧑‍💻 What We’re Looking For** ### Core Requirements - **3–6 years** of experience in data science, analytics, or marketing science. We'll flex level and title based on candidate strength. - **Strong SQL and Python** — comfortable working with data end-to-end without hand-holding. - **Meaningful experience supporting a marketing, growth, or lifecycle team** — you understand how marketers think and what decisions they need data to make. - **At least one measurement specialty done well**: experimentation/incrementality, attribution, MMM, marketing analytics, or growth analytics. You don't need all of them — you need one that you're actually good at. - **Strong product/business intuition** — you can look at a dashboard and know what's worth chasing. - **Excellent communication** — you can tell a clear data story to a marketer, a PM, or a CFO, and hold your own in a room with strong opinions. - **High ownership and comfort in ambiguity** — you can figure out what needs doing and go do it. What You'll Grow Into We don't expect you to walk in with all of the below — but if you find these interesting and want to build depth here, this role is a great place to do it: - Full-stack marketing attribution architecture (taxonomy, windows, multi-model, priority logic) - MMM (build, buy, or vendor-partner) - Instrumentation and UTM/tracking design at platform level - Cross-channel spend strategy and marketing direction ### Nice to Have - Experience measuring **influencer/creator/UGC marketing** - Experience as an early or first data hire supporting a marketing org. - Familiarity with our stack: BigQuery, Amplitude, Metabase, Stripe, Google/Meta/TikTok/Bing/Reddit Ads, GTM, Impact, Tolt. - Experience in consumer product, marketplaces, creator platforms, or e-commerce. - Exposure to AI/ML products or generative AI. - Familiarity with privacy-era measurement (Consent Mode, SKAN/ATT, Privacy Sandbox). **⚙ Tech Stack You’ll Work With** BigQuery, SQL, Python, Amplitude, Metabase, Stripe, Google Ads, Meta Ads, TikTok Ads, Bing Ads, Reddit Ads, Linkedin Ads, GTM, Impact, Tolt, GCP **💰 Compensation** - Competitive base salary and bonus program - Equity — meaningful ownership in what you build - High autonomy, high growth environment **🌍 Work Setup** - Bay Area preferred (hybrid allowed) - Visa sponsorship available - We’ll