Staff Data Scientist

Job Lead

High-impact data science initiatives across marketing, growth, and product, from problem definition through methodology, execution, interpretation, and recommendation.

Define org-level technical strategy

Identify high-leverage opportunities, and establish best practices for experimentation, causal measurement, modeling, AI-assisted development, and decision science.

Design, analyze, and interpret experiments and quasi-experiments

Build scalable frameworks to estimate incrementality, treatment effects, and long-term business value.

Develop ML, uplift, heterogeneous treatment effect, and adaptive experimentation models

To improve targeting, segmentation, personalization, lifecycle optimization, audience strategy, budget allocation, and product decisions.

Partner with Marketing, Growth, Sales, Finance, and Product

Evaluate acquisition, retention, ROI, user journeys, funnels, marketplace dynamics, donation conversion, and engagement.

Use AI tools to accelerate prototyping, analysis, coding, debugging, documentation, and repetitive workflows

Without compromising quality, accuracy, or review standards.

Translate complex analyses into clear recommendations

For technical, non-technical, and executive audiences.

Collaborate with Data, Analytics, and Product Engineering

To improve instrumentation, data quality, experimentation infrastructure, and reusable data science workflows.

Mentor data scientists and analysts

Through design reviews, model reviews, methodology discussions, AI-enabled workflows, and shared best practices.

Preferred Experience

• With marketing measurement methods such as media mix modeling, multi-touch attribution, channel incrementality, forecasting, budget allocation, optimization, or ROI modeling.
• Experience with web, mobile, product, or marketplace analytics tools such as Amplitude, Google Analytics, Optimizely, or GrowthBook.
• Familiarity with modern data platforms and workflows such as Snowflake, Databricks, dbt, Airflow, Git, Looker, Tableau, or similar tools.
• Experience operationalizing AI or ML workflows with engineering partners.