Data Scientist, Marketing

User Acquisition

Build and maintain robust ETL pipelines that ingest, transform, and validate UA data from ad networks, MMPs, and internal systems.

Develop and refine predictive LTV (pLTV) models to enable faster optimization of UA campaigns based on early user signals.

Explore, develop, and refine AI-based systems that are able to answer common data inquiries from stakeholders, as well as quickly diagnose data pipeline issues, etc.

Contribute to marketing mix modeling (MMM) and other aggregate measurement approaches to evaluate cross-channel and upper-funnel impact (e.g. brand) where deterministic attribution is limited.

Partner with Finance and UA teams to align on forecasting methodologies and investment strategies driven by pLTV and payback periods.

Direct Marketing

Build and maintain reliable datasets and ETL workflows that ingest and transform marketing data from ad platforms, CRM systems, social channels, and internal data sources.

Support measurement and optimization of direct marketing channels including email, push notifications, in-app messaging, and other CRM/lifecycle campaigns.

Partner with Marketing stakeholders to provide actionable insights on targeting, segmentation, messaging effectiveness, and channel strategy.

Analytics Infrastructure & Workflow Efficiency

Contribute to scalable dashboards and standardized reporting that enable self-serve marketing analytics.

Ensure data quality, documentation, and consistency across marketing data pipelines.

Leverage modern AI/ML tools (e.g., automated modeling workflows, AI coding assistants) to improve analysis speed, code quality, and documentation.

Identify opportunities to automate recurring reporting and insight generation for marketing stakeholders.

Contribute to responsible and thoughtful adoption of AI-powered analytics tools.