Marketing Data Scientist

Description

The company runs an AI storytelling and visual creation platform used by millions of people. It builds creative tools that let users make videos, visuals, characters and stories quickly with generative AI.

This is the first dedicated marketing data scientist role. You will work with the Head of Data to measure, test and explain results across performance marketing, influencer and UGC, and lifecycle email. You do not need to be an expert in every part of marketing science. The Head of Data has done this work before and will coach you on the harder parts.

You will pick up work already underway, including the multi-model attribution build, the attribution alignment effort with the marketing team, and live incrementality tests on Google brand versus non-brand and an email upsell holdout. You will also lead areas with little coverage so far, especially real-time influencer and UGC measurement, which is a major gap and a top priority.

Responsibilities

• Own the weekly marketing review with the influencer team by bringing the data, your interpretation and a recommendation.
• Build and maintain real-time dashboards for influencer and UGC traffic spikes, CAC, ROAS and payback by channel, and performance by campaign.
• Find and fix attribution gaps between ad platforms, the warehouse and the CRM, including the current Meta attribution gap, Impact Radius and Google Ads conversion tracking work.
• Design and run incrementality, holdout and A/B tests across email, paid channels and, where practical, influencer marketing.
• Help design and analyse the HDYHAU survey to correct platform-reported CAC.
• Run deep dives that guide spend, such as creative analysis, cohort and LTV analysis, channel efficiency and campaign post-mortems.
• Help build the attribution model: channel, subchannel and partner taxonomy, attribution windows, priority rules, promo code handling and multi-model attribution.
• Help instrument per-creator attribution with unique codes, UTMs and landing pages.
• Take on ownership of these areas over time as your depth grows.
• Turn findings into clear, firm recommendations that marketing leaders act on, both in writing and in meetings.
• Set the standard for experiment rigour and measurement quality across marketing.
• Growth areas, not expected on day one: full-stack attribution architecture, MMM built in-house, bought or through a vendor, platform-level UTM and tracking design, and cross-channel spend strategy with marketing direction.

Requirements

• 3 to 6 years of experience in data science, analytics or marketing science. Level and title depend on your strengths.
• Strong SQL and Python, and able to take data from start to finish on your own.
• Solid experience supporting a marketing, growth or lifecycle team, with a clear sense of the decisions marketers need data for.
• Real skill in at least one measurement area: experimentation or incrementality, attribution, MMM, marketing analytics or growth analytics. You do not need all of them.
• Good product and business judgement, with the ability to spot what on a dashboard is worth pursuing.
• Clear communication with marketers, product managers and finance leaders, and confidence defending your view in the room.
• High ownership and comfort with ambiguity, so you can work out what needs doing and do it.
• Experience measuring influencer, creator or UGC marketing.
• Experience as an early or first data hire supporting a marketing team.
• Familiarity with the stack: BigQuery, Amplitude, Metabase, Stripe, Google, Meta, TikTok, Bing and Reddit ads, GTM, Impact and Tolt.
• Experience in consumer products, marketplaces, creator platforms or e-commerce.
• Exposure to AI or ML products, or to generative AI.
• Familiarity with privacy-era measurement such as Consent Mode, SKAN/ATT and Privacy Sandbox.
• Tools you will use: BigQuery, SQL, Python, Amplitude, Metabase, Stripe, Google Ads, Meta Ads, TikTok Ads, Bing Ads, Reddit Ads, LinkedIn Ads, GTM, Impact, Tolt and GCP.

Conditions

Competitive base salary and a bonus program.

Equity, giving you meaningful ownership in what you build.

High autonomy in a high-growth environment.

Bay Area preferred, with hybrid work allowed.

Remote work considered for exceptional candidates only.

Visa sponsorship available.

Benefits

• Join during a steep growth phase: revenue has grown 7 to 10X over the past 2 years in AI-native creative tools, one of the hottest areas in tech.
• Run the data science behind one of the company's biggest growth levers, marketing spend across influencer, paid and lifecycle.
• Work with marketing, growth, product, data engineering and finance in one of the most cross-functional roles at the company.
• Help build from zero: the attribution model, channel taxonomy and measurement stack are being set up now, and you will help finish them and then run them.
• Work with high ownership, little process and fast iteration.