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Raphael David

@raphaeldavid

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Data scientist and decision scientist using causal, marketing analytics to drive revenue growth.

United States

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What I'm looking for

I’m looking for a role where I can apply causal and experimentation-driven analytics to growth and revenue problems, work closely with stakeholders, and keep building production-grade models and dashboards that translate into clear, measurable decisions.

I’m a Decision Scientist and Data Scientist who turns messy customer and marketing data into measurable business impact. At Kobie, I manage loyalty analytics end-to-end, built a synthetic control incrementality model for a paid loyalty tier, and developed a personalized offer targeting engine in PySpark that increased offer redemption rates by 2x.

Previously at Marketbridge, I led growth marketing optimization with A/B testing (including a Python MMM-like marketing spend simulator) and helped drive a 4% year-over-year lift and $1.2M in incremental revenue, improving campaign ROI by 11%. I also bring automation and clear communication—simplifying data insights for non-technical stakeholders—and I’m equally comfortable in Python, SQL/BigQuery, and cloud analytics with AWS tools.

Experience

Work history, roles, and key accomplishments

Current

Decision Scientist

Current

Kobie

Oct 2025 - Present (9 months)

Managed loyalty analytics projects and client relationships for global retail and telecom brands. Built a synthetic control-based incrementality model and developed a PySpark personalized offer targeting engine to improve redemption rates and campaign ROI.

Loyalty Analytics Synthetic Control Incrementality Client Relationship Management Pyspark

Data Scientist

Marketbridge

Mar 2024 - Oct 2025 (1 year 7 months)

Developed and executed growth marketing strategies using A/B testing to optimize conversion efforts and increase lift. Owned a Python marketing spend simulator using causal lift estimation and diminishing-returns response curves to quantify marginal ROAS and improve campaign ROI.

A B Testing Growth Marketing Conversion Optimization Marketing Mix Modeling Diminishing Returns Modeling Python Marketing Analytics

Marketing Data Scientist (contract)

Dovly

Mar 2023 - Dec 2023 (9 months)

Analyzed freemium user behavior for a credit repair product to identify key conversion and feature-related pain points. Collaborated on a data-driven retention strategy and automated cost reporting workflows using Python and AWS Lambda.

User Behavior Analysis Customer Retention Customer Segmentation Python AWS Lambda

Data / Business Operations Analyst

Culdesac

Oct 2021 - Oct 2022 (1 year)

Led analytics for the launch of a weekly pop-up market, partnering with local vendors to drive engagement. Used SQL and Looker to optimize community features and automate dashboards for resident satisfaction and transportation usage to support product decisions.

Analytics Leadership SQL Looker Dashboarding Community Analytics Automation

Moneyball for Farmers Markets

ASU Food and Agribusiness Lab

Developed and optimized a recommendation system using predictive analytics and machine learning to curate an ideal vendor mix for a farmers market. Balanced shopper preferences with vendor profitability to project improved budget efficiency while maintaining the market’s character.

Recommendation Systems Predictive Analytics Machine Learning Vendor Selection