I build the analytics, automations, scoring models, dashboards, and operating rhythms that help teams understand customers, improve lead flow, and make sharper product and revenue decisions.
These projects show the operating layer behind the dashboards: data pipelines, CRM logic, automation, statistical modeling, and decision tools.
Built a connected operating layer for lead scoring, routing, rep efficiency, performance monitoring, probation workflows, dashboards, services, and integrations.
Unified web analytics, CRM activity, and sales data to quantify channel influence across the full customer funnel.
Built and maintained multi-channel outreach logic across the customer journey with cleaner handoffs and leadership visibility.
Modeled behavioral constructs behind engagement and retention to surface product gaps and guide audience targeting.
Built reporting surfaces that connect marketing funnels, sales operations, product engagement, and leadership decisions.
Turned noisy, multi-source business questions into statistical deep dives, visual evidence, and action-ready recommendations.
My background in behavioral science shapes how I build systems: define the behavior, instrument the process, measure the outcome, and improve the loop.
Lead scoring, intelligent routing, rep efficiency monitoring, probation systems, CRM administration, lifecycle design, and KPI operating rhythms.
Predictive modeling, regression, multivariate analysis, attribution, factor analysis, and structural equation modeling.
BigQuery, Snowflake, SQL, Sigma, Salesforce, Google Analytics, data joins, dashboards, and scalable reporting systems.
Survey design, longitudinal analysis, customer feedback, user research, publications, and evidence-based recommendations.
Currently leading product, marketing, and revenue analytics work at AlterMe while completing a Master of Statistics at the University of Utah.
Own product and marketing analytics, revenue operations systems, lead scoring, intelligent routing, KPI systems, attribution modeling, and lifecycle automation.
Collected longitudinal client data and supported behavioral progress through applied behavioral analysis work.
Analyzed social psychology data, supported published research, taught inferential statistics, and helped students present research.
Product analytics, marketing analytics, Revenue Operations, lead scoring, intelligent routing, attribution, customer lifecycle automation, and KPI systems.
Ongoing graduate work in regression, structural equation modeling, inference, and advanced statistical analysis.
Experience in social psychology, longitudinal research, survey design, behavioral analysis, and statistical communication.
I am interested in data science, Revenue Operations, product analytics, marketing analytics, and roles where customer behavior meets business outcomes.
A connected operating system for revenue operations: predictive lead scoring, intelligent routing, rep efficiency monitoring, performance dashboards, probation and coaching signals, services, integrations, and admin workflows.
Revenue operations work was spread across admin tasks, dashboards, routing logic, rep performance questions, coaching needs, and fragmented handoffs. Leadership needed a clearer way to see where process friction was costing revenue motion.
I built a functioning lead probability and scoring model, connected it to smarter routing logic, standardized calendars and handoffs, and created monitoring systems for rep efficiency, performance trends, and probation/coaching workflows.
The platform made lead ownership clearer, gave reps and managers better visibility into performance, improved response capacity, and turned RevOps from cleanup work into a measurable growth lever.
A custom multi-touch attribution model that connected acquisition, CRM activity, and transaction data so marketing decisions could be tied to full-funnel outcomes.
Channel performance was hard to evaluate because web analytics, Salesforce activity, and purchase outcomes lived in separate systems.
I unified source, behavioral, demographic, CRM, and transaction fields into an analysis-ready table and used logistic regression to estimate conversion probabilities.
Leadership got a clearer view of which marketing and CRM paths were associated with higher conversion, creating more concrete targets for budget allocation and CPA improvement.
A multi-channel outreach system built inside Salesforce to make customer communication more consistent across the full journey.
Customer outreach needed to be consistent and sequenced, but the journey had too many manual touchpoints and too little visibility for leadership iteration.
I mapped the cadence visually, implemented Salesforce Flow logic, connected webhooks, and maintained the system as the customer journey evolved.
The automation improved consistency across the journey, reduced manual coordination, and gave the business a cleaner mechanism for testing and improving lifecycle communication.
A large-scale SEM project connecting user behavior and analytics data to model retention and guide product improvements.
User retention was influenced by less-visible behavioral constructs that could not be understood from surface metrics alone.
I modeled latent constructs for excitement, engagement, and issues, then connected those constructs to tangible retention outcomes.
The model surfaced a product-expectation gap and helped guide onboarding, retention, and top-of-funnel audience strategy.
A sample gallery of analytical and exploratory reporting views used to clarify performance, surface trends, and support operating decisions.
Teams needed scannable reporting that connected operational performance to practical decisions instead of burying signal in raw exports.
I built dashboards and visualizations around KPIs, performance patterns, and trend interpretation for leadership and operators.
Dashboards made funnel, sales, and customer signals more visible, helping stakeholders align on where performance was changing and why.
A statistical deep dive into conversion-rate changes, with visualized KPIs, trend interpretation, and recommendations for business action.
A negative conversion-rate trend needed explanation, but the causes were spread across unrelated operational and customer data points.
I identified KPIs, compared business periods, separated noise from meaningful differences, and translated the analysis into recommendations.
The report turned a broad stakeholder concern into an evidence-backed decision path with clearer tradeoffs and action items.