05/12/2026 updated
100 % available
Media Mix Modeling, Causal Lift, Hierarchical Bayesian Models // Ex-Tinder, Analytic Partners
San Marino, USA
Only remote
Bachelor of Science in Economics, University of California, Berkeley (May 2013)About me
MMM architect at Tinder (hierarchical Bayesian, Stan/Python, global media budget). Causal inference, geo holdouts, incrementality. 8+ years. Analytic Partners background. I'm a bridger -- I don't build in isolation. & I have a knack for finding the narrative thread to push recos through.
Business IntelligenceExtract Transform Load (ETL)Design of ExperimentsForecastingR (Programming Language)Python (Programming Language)Marketing Mix ModelingMarketing AnalyticsMultivariate AnalysisPredictive AnalyticsSensitivity AnalysisStructural Equation ModelingSalesforce TableauRoot Cause AnalysisFeature Engineering
Marketing Mix Modeling (MMM) & Bayesian Analytics
Expertise in Media Mix Modeling (MMM), hierarchical (multilevel) Bayesian models, causal lift measurement, and Bayesian media mix modeling to support investment decisions at scale, including the design and productionalization of hierarchical Bayesian MMM models with varying intercepts and slopes.
Programming & Statistical Tools
Proficiency in Python, SQL, R, and STAN for data analysis, statistical modeling, scenario planning, and strategic marketing decisions, including building probabilistic pipelines for uncertainty quantification.
Data Visualization & Reporting
Strong command of Tableau and Plotly for building operational reporting dashboards, interactive data visualizations, and executive-ready reporting to support decisions across marketing, finance, product, CRM, and trust and safety initiatives.
Data Warehousing, Platforms & Orchestration
Hands-on experience with Redshift, Databricks, Mode, and dbt for data orchestration, pipeline management, and scalable analytics infrastructure.
Causal Inference & Quasi-Experimental Design
Application of geo-lift tests, forced on/off variation, difference-in-differences (DiD), and incrementality methods to ensure budget and optimization decisions are consistent with observed incrementality.
Time Series Forecasting & Scenario Simulation
Use of Prophet and other time series forecasting methods alongside scenario simulation and incrementality analysis to inform long-term strategic planning.
ETL Development & Automation
Authoring and automating ETL processes in SQL and R that power reporting and data visualization layers for over $100MM in annual media spend, including customer segmentation insights delivered via Tableau dashboards.
Econometrics & Structural Equation Modeling
Development and presentation of Structural Equation Models and econometric analyses to forecast digital conversion targets and generate impactful, data-informed recommendations for senior business leaders.
Business Intelligence & Scalable Analytics Infrastructure
Leadership in global BI rollouts to create scalable infrastructure for reporting and analytics across research, marketing, and media measurement platforms serving thousands of users.
Expertise in Media Mix Modeling (MMM), hierarchical (multilevel) Bayesian models, causal lift measurement, and Bayesian media mix modeling to support investment decisions at scale, including the design and productionalization of hierarchical Bayesian MMM models with varying intercepts and slopes.
Programming & Statistical Tools
Proficiency in Python, SQL, R, and STAN for data analysis, statistical modeling, scenario planning, and strategic marketing decisions, including building probabilistic pipelines for uncertainty quantification.
Data Visualization & Reporting
Strong command of Tableau and Plotly for building operational reporting dashboards, interactive data visualizations, and executive-ready reporting to support decisions across marketing, finance, product, CRM, and trust and safety initiatives.
Data Warehousing, Platforms & Orchestration
Hands-on experience with Redshift, Databricks, Mode, and dbt for data orchestration, pipeline management, and scalable analytics infrastructure.
Causal Inference & Quasi-Experimental Design
Application of geo-lift tests, forced on/off variation, difference-in-differences (DiD), and incrementality methods to ensure budget and optimization decisions are consistent with observed incrementality.
Time Series Forecasting & Scenario Simulation
Use of Prophet and other time series forecasting methods alongside scenario simulation and incrementality analysis to inform long-term strategic planning.
ETL Development & Automation
Authoring and automating ETL processes in SQL and R that power reporting and data visualization layers for over $100MM in annual media spend, including customer segmentation insights delivered via Tableau dashboards.
Econometrics & Structural Equation Modeling
Development and presentation of Structural Equation Models and econometric analyses to forecast digital conversion targets and generate impactful, data-informed recommendations for senior business leaders.
Business Intelligence & Scalable Analytics Infrastructure
Leadership in global BI rollouts to create scalable infrastructure for reporting and analytics across research, marketing, and media measurement platforms serving thousands of users.
Experience
Professional experience5 - 10 years
Freelancer since2026
Languages
EnglishNative speaker
Project history
Owned and evolved Tinder's global marketing measurement stack, defining a tiered strategy spanning self-serve reporting, campaign-level causal lift measurement, and Bayesian media mix modeling to support investment decisions at scale. Designed and productionalized a hierarchical Bayesian MMM model to inform scenario planning and strategic marketing decisions guiding a $140MM annual global marketing budget. Catalyzed ~30-80% budget reallocations away from underperforming channels, delivering an 18% increase in ROAS for the largest brand campaign. Incorporated experimental results as constraints on MMM assumptions and built a custom Bayesian augmented synthetic control model for campaign-level causal lift measurement.
Generated impactful, data-informed recommendations for senior business leaders on marketing execution and strategy for a big four Australian bank with a $60MM+ annual marketing budget, using MMM and other statistical tools to separate baseline demand from media-driven effects. Led a team of 2 analysts to deliver quarterly econometric analyses yielding over $70MM in incremental revenue. Developed, tested, and presented a Structural Equation Model for the Head of Digital to forecast digital conversion targets.
Structured ambiguous problems and designed analyses for senior leadership to drive actionable insights ranging from strategic planning to marketing campaign and operational optimizations. Oversaw 3 operations managers to fine-tune marketing and call center operations with data-backed hypotheses amounting to ~$25,000 in weekly incremental profit. Designed and built an operational reporting dashboard in Tableau. Developed new business-critical KPIs and performed extensive ad-hoc analyses using SQL.