Data Science + Revenue Operations

Revenue operations, powered by data science.

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.

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Salesforce flows BigQuery + Snowflake Sigma dashboards Attribution modeling Customer lifecycle systems
40% higher revenue lead efficiency through routing, handoffs, and calendar logistics
20% team efficiency lift from rep monitoring, coaching, and workflow design
15+ predictive and attribution models built for funnel and conversion decisions
30% customer engagement and retention lift through lifecycle automation
Featured Projects

Systems that make revenue teams run better.

These deep dives focus on the operating layer behind the metrics: Salesforce tooling, predictive models, routing logic, manager visibility, marketing quality analysis, and behavioral feedback loops.

Flagship 01 Salesforce Rep Enablement AI Review

Salesforce Workcenter + Rep Enablement System

A custom CRM workcenter that gives reps one place to manage leads, daily schedules, action history, personal stats, training insights, leaderboard context, AI call reviews, and smart meeting coverage.

2xoverall rep efficiency after adoption
50%reduction in missed customer communication
Livepersonalized training loop from stats and calls
Rep-facing operating system for lead management, training, coverage, and accountability
Redacted preview of Salesforce workcenter lead management screen Preview of training insights and suggested actions Preview of AI call review and quality score Preview of rep stats page
Flagship 02 Manager Tools Performance Ops Probation Workflows

Manager Console + Performance Operations System

A live floor-activity console for managers and remote stakeholders, combining activity monitoring, probation controls, historical action review, and KPI leaderboards into a consolidated management layer.

Live viewremote visibility into rep status and floor activity
Controlsopportunity limits tied to performance flags
KPI pickerrankings for coaching, PIPs, and training decisions
Manager-facing visibility that distinguishes effort problems from skill gaps
Redacted preview of manager activity console Redacted preview of manager performance leaderboard Redacted preview of manager probation controls
Flagship 03 Marketing Analytics Lead Quality Predictive Modeling

Marketing Analytics + Lead Quality Intelligence

A marketing analytics layer connecting campaign performance, UTM/event testing, lead quality, predictive close likelihood, pricing analysis, ad spend pacing, and revenue-impact decisions.

14%stronger revenue event signal from a tested optimization
Qualitymonitoring by campaign, source, and medium
CPApricing and placement analyses for better tradeoffs
Growth analytics that connects marketing volume to lead quality, routing, and revenue
Preview of pricing analysis chart
Preview of smart lead throttle configuration
Model to Ops Lead Scoring Capacity Planning

Predictive Lead Routing + Smart Lead Throttle

A bridge between marketing analytics and revenue operations: close-likelihood prediction, capacity-aware lead release, booking-rate assumptions, and routing logic that controlled flow into the sales team.

Within 2%predicted lead closing odds
+40%daily sale opportunity capacity
+20%revenue increase from smarter routing
Predictive modeling connected directly to routing, scheduling, and revenue capacity
Research Behavior NLP

Academic & Behavioral Research

My research background gives my operations work a stronger measurement standard. I have worked across biometric data, wearable devices, loneliness, social connection and diverse scales, language toxicity, network ties, and behavioral analysis, often linking combinations of these to find and explore new outcomes.

Measurement discipline behind the operating systems

Two-way integrations

Outlook/Salesforce, Intercom/Salesforce, Intercom/Shopify, and Twilio/Salesforce integrations for cleaner employee and customer workflows.

Review gathering automation

Smart review collection workflows that improve reputation signals and automate post-customer touchpoints.

Ad-hoc decision analytics

Analyses across text cadence, lifecycle email efficiency, contractor cost/benefit, survey writeups, and shareholder KPI reporting.

Pricing optimization

Statistical product split, pricing, and placement analyses to identify stronger conversion, lead quality, and CPA tradeoffs.

Behavioral performance design

Psychology-informed peer benchmarking, social proof, and accountability loops to improve rep performance and team standards.

SEM retention analysis

Structural equation model path diagram for engagement and retention analysis

Structural equation modeling and customer behavior analysis that connect latent engagement signals to product and retention decisions.

Operating strengths

Revenue systems with a researcher's standard for evidence.

My background in behavioral science shapes how I build systems: define the behavior, instrument the process, measure the outcome, and improve the loop.

Revenue Operations

Lead scoring, intelligent routing, rep efficiency monitoring, probation systems, CRM administration, lifecycle design, and KPI operating rhythms.

Data Science

Predictive modeling, regression, multivariate analysis, attribution, factor analysis, and structural equation modeling.

Analytics Engineering

BigQuery, Snowflake, SQL, Sigma, Salesforce, Google Analytics, data joins, dashboards, and scalable reporting systems.

Behavioral Research

Survey design, longitudinal analysis, customer feedback, user research, publications, and evidence-based recommendations.

Resume highlights

Built for roles where analytics, operations, and strategy have to move together.

Currently leading product, marketing, and revenue analytics work at AlterMe while completing a Master of Statistics at the University of Utah.

2024 - Present

Lead Operations & Marketing Data Scientist, AlterMe

Own product and marketing analytics, revenue operations systems, lead scoring, intelligent routing, KPI systems, attribution modeling, and lifecycle automation.

2023 - 2024

Autism Research Aide, Wasatch Behavioral Health

Collected longitudinal client data and supported behavioral progress through applied behavioral analysis work.

2020 - 2023

Research and Teaching, Brigham Young University

Analyzed social psychology data, supported published research, taught inferential statistics, and helped students present research.

Curriculum Vitae Open PDF
Current focus Lead Operations & Marketing Data Scientist

Product analytics, marketing analytics, Revenue Operations, lead scoring, intelligent routing, attribution, customer lifecycle automation, and KPI systems.

Education Master of Statistics, University of Utah

Ongoing graduate work in regression, structural equation modeling, inference, and advanced statistical analysis.

Research foundation Behavioral science and published research

Experience in social psychology, longitudinal research, survey design, behavioral analysis, and statistical communication.

Contact

Want the operator who can also build the measurement system?

I am interested in data science, Revenue Operations, product analytics, marketing analytics, and roles where customer behavior meets business outcomes.

Email me Ask my resume
Case study
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Salesforce Workcenter + Rep Enablement System

I built a custom Salesforce workcenter for lead management and closing leads, giving reps one operating surface for leads, daily schedules, action history, personal stats, training insights, leaderboards, AI call review, and meeting coverage.

Salesforce Lead management Rep enablement AI call review Peer benchmarking Training insights
2xoverall rep efficiency after adoption
50%reduction in missed customer communication
Continuouspersonalized training from stats, calls, and notes
Redacted preview of Salesforce workcenter lead management screen Preview of training insights and suggested actions Preview of AI call review and quality score Preview of rep stats page

Problem

Rep work was fragmented across lead lists, outreach tools, schedules, call history, manager feedback, and performance context. That fragmentation slowed action and made coaching reactive.

What I Built

A one-stop workcenter with action history, personal record and stats pages, daily schedule overviews, suggested actions, scheduled event aggregation, training meetings, and live-updating leaderboards.

Training Intelligence

The training system compares reps with floor benchmarks and top performers, identifies behavioral and statistical gaps, and turns call reviews and notes into practical improvement feedback.

Coverage Logic

I also built smart meeting coverage so reps with calls running long could release calls for other reps to claim, improving efficiency and reducing missed opportunities.

Impact

After adoption, overall rep efficiency doubled, missed customer communication was cut in half, and rep performance improved as personalized training became part of the workflow.

Why It Matters

This is the clearest example of my RevOps style: build the system, instrument the behavior, feed the signal back to the team, and make performance improvement operational.

Manager Console + Performance Operations System

I created a manager-facing console that turns live rep activity, probation controls, historical actions, and KPI rankings into a consolidated view of floor efficiency and team effort.

Manager tooling Performance operations Probation workflows Historical activity KPI leaderboard
Live floor viewremote visibility into rep status, activity, and capacity
Probationsstructured controls for limiting opportunities when needed
Any KPIranked stat picker for coaching and performance decisions
Redacted preview of manager activity console Redacted preview of manager performance leaderboard Redacted preview of manager probation controls

Problem

Managers needed the equivalent of watching the sales floor over a rep's shoulder, including remote visibility for stakeholders who were not physically present.

Activity Console

The live activity tab consolidates rep status, schedules, current and next meetings, Twilio activity, Salesforce actions, and productivity signals into one operating view.

Probation Controls

The probation tab makes it easy to limit a rep's opportunities when they are flagged for poor performance by other systems, keeping coaching decisions tied to evidence.

Historical Review

Managers can review everything selected groups or individuals did over a given period, helping distinguish low performance caused by effort from low performance caused by skill gaps.

Performance Ranking

The leaderboard and stat picker rank reps by selected KPIs, supporting informed decisions on probations, PIPs, and tailored training.

Business Value

The console makes management more proactive: risk is visible earlier, good performance is easier to spot, and coaching can be pointed at the right behavior.

Marketing Analytics + Lead Quality Intelligence

I built marketing analytics around lead quality, campaign/source/medium performance, UTMs, pricing decisions, ad pacing, predictive close likelihood, and revenue impact.

Sigma Salesforce UTMs Lead quality Pricing analysis Predictive modeling
14%more effective tested event signal than the existing model
Quality over timecampaign, source, and medium monitoring
Revenue lensmarketing choices connected to close probability and routing
Preview of pricing analysis chart

Problem

Marketing reporting needed to move beyond volume. The business needed to know which campaigns and channels produced high-quality leads that actually converted.

What I Built

I created dashboards and recurring analyses in Sigma and Salesforce to track quality trends, pacing to targets, campaign performance, and revenue-relevant lead outcomes.

Model Connection

The lead probability model gave marketing a quality lens: campaign and event performance could be evaluated by predicted close likelihood, not just form fills or traffic.

Event Optimization

For a new event, I set up UTMs and connected inbound traffic and leads to the model. The new event measured 14% more effective than the existing model, supporting a strict 14% revenue lift with universal adoption.

Pricing and CPA

I ran pricing and placement analyses to find tradeoffs that minimize CPA while maximizing lead quality and conversion opportunity.

Strategic Role

The work informed campaign priorities, product and sales direction, budget allocation, and the routing logic that turns marketing signal into sales capacity.

Predictive Lead Routing + Smart Lead Throttle

I connected a lead probability model to operational routing and capacity planning so leads could be released and prioritized intelligently instead of flowing blindly into the team.

Lead scoring Capacity planning Routing prioritization Calendar systems Sales logistics
Within 2%predicted a lead's odds of closing
+40%daily sale opportunity capacity
+20%revenue increase from smarter routing
Preview of smart lead throttle configuration

Problem

Lead volume, sales capacity, booking probability, and calendar availability needed to be balanced instead of treated as separate operational problems.

Predictive Model

I created a predictive model that estimated a lead's odds of closing within 2%, then used that probability to inform routing decisions.

Smart Throttle

The throttle released leads based on rep capacity and predicted booking rates, helping the team avoid overwhelming reps while still maximizing opportunity coverage.

Logistics Layer

Alongside the model, I restructured calendars for performance-based meeting allocation and prioritization, standardized shifts, and enabled overbookings.

Impact

The combined system increased daily sale opportunity capacity by 40% and produced a 20% revenue increase through smarter routing.

Why It Matters

This project shows the full arc: statistical prediction, CRM logic, capacity planning, and measurable revenue operations impact.

Academic & Behavioral Research

My research background gives my operations work a stronger measurement standard. I have worked across biometric data, wearable devices, loneliness, social connection and diverse scales, language toxicity, network ties, and behavioral analysis, often linking combinations of these to find and explore new outcomes.

4,563talk interactions analyzed in pilot thesis data
627unique editors in the Wikipedia toxicity study
98%lower toxic-utterance odds for a fully reciprocal editor in the model

Pilot Thesis Data

I analyzed shock events, network ties, and discourse toxicity on Wikipedia talk pages using page-view validation, talk-page interactions, reciprocal network proxies, and NLP-based toxicity scoring.

Finding

The evidence suggested shock events diluted the community with outsiders more than they radicalized insiders, while reciprocal interaction networks were associated with lower toxicity.

Broader Research

Beyond that project, my academic work includes biometric data, wearable devices, loneliness, social connection, diverse scales, behavioral measurement, and how combinations of those signals can reveal new outcomes.

How It Transfers

That background shapes how I build business systems: define the behavior, instrument the process, test the signal, and communicate limitations clearly.

That research habit shows up in my business work: I look for the behavioral signal underneath the operational metric, then test whether the measurement is strong enough to guide a real decision.