Career Accomplishments • Apr 2026

13 years of measurement infrastructure for revenue and marketing teams.

I build the pipelines, dashboards, attribution, and lead-scoring layer from the ground up — then use it to compound growth. Below: the track record, role by role, with the outcome and the approach that produced it.

Salt Lake City, UT 801-850-1253 sthill01@gmail.com linkedin.com/in/sthill
+250%
Mid-Funnel Lift
Netgain, 6-product SaaS
−60%
CAC Reduction
Website Squirrel lead scoring
72hrs/wk
Reporting Eliminated
Foxit eSign Python ETL
3×
ROI in a Quarter
Foxit unified data layer
Four Themes Across Every Role

What I build, end to end.

Each pillar below spans multiple companies and industries — the common thread is instrumenting and operationalizing the measurement layer, not just reporting on top of whatever exists.

Data Infrastructure & Automation

Python / SQL / AWS pipelines
  • 72 hrs/wk of manual executive reporting eliminated at Foxit via automated Python infrastructure — fueled 3× quarterly ROI.
  • 15 hrs/wk of manual reporting removed at Website Squirrel through Python pipelines on AWS.
  • SQL lead-scoring and customer-segmentation models across CRM + transactional + behavioral data at multiple companies.
  • Unified product, billing, support, marketing into one reconciled source of truth at Foxit (first time leadership had one).

Attribution & Measurement

Multi-touch models • ROAS • CAC
  • Owned online + offline multi-touch attribution across a 6-product SaaS portfolio at Netgain, driving weekly exec reporting and budget allocation.
  • Attribution dashboards informing $50M+ in client media spend at RGM Group (performance agency).
  • Granular ROI analysis across 48+ campaigns at Website Squirrel, surfacing durable repeat-revenue patterns.
  • ARIMAX forecasting models at UTA projecting fare-structure demand, revenue, and outcome probabilities for exec policy decisions.

Paid Channel Optimization & CAC

Acquisition efficiency
  • 60%+ lead CAC reduction at Website Squirrel through automated lead-scoring + behavioral segmentation + targeted nurture.
  • 250% mid-funnel lift at Netgain via "Moments that Matter" NSM isolation and high-velocity testing sprints.
  • 62% ad-response uplift with 25% ACoS reduction on B2B demand gen at Tuff Toe (ABM + marketing automation).
  • Led 6-person Growth team + 8-person cross-functional team running high-velocity paid experiments at Foxit.

Funnel Conversion & Revenue Impact

Full-funnel revenue
  • Doubled app conversion at Healthicity by rebuilding product-tracking analytics — 50% reduction in lead times.
  • 68% YoY B2B growth + 20% organic traffic growth at Tuff Toe via ABM, content, automation.
  • Social audience 400% in two months at Healthicity (rebrand launch).
  • Analyzed 20+ usage datasets at Netgain surfacing product and cross-sell opportunities.
Role-by-Role Timeline

The work, in sequence.

Each role is styled in the visual language of the company it was built for. Every STAR snapshot below is a signature story from that engagement.

IV
Independent Trading Venture
Market Analyst & Quantitative Equity Trader
Feb 2025 → Present

Full portfolio-analytics, research & data-engineering stack, solo.

Running full portfolio management, research, and data engineering for an active quantitative equity trading operation. Responsible for pipeline architecture, systematic strategy design, backtesting, live trading infrastructure, risk management, and reporting.

Key Accomplishments
  • Built end-to-end portfolio analytics stack from scratch — data ingestion, factor modeling, backtesting, live trading, reporting — in under 3 months with zero external dependencies.
  • Automated reconciliation + risk controls dropped position errors and drawdown violations from 5+/month to zero.
  • Factor-based equity screening framework ranks 500+ stocks weekly across value, quality, momentum.
  • Production-grade Power BI dashboard: real-time P&L, Sharpe, factor exposure, daily drawdown monitoring.
  • Statistical regime analysis reduced strategy drawdown by 40% during market dislocations.
Highlighted Story
Built a production-grade quant trading stack in 8 weeks.

Situation. Strong Python fundamentals, zero existing infrastructure; needed data ingestion, backtesting, live trading, dashboards, and risk controls with statistical rigor.

Action. Architected five layers: data, research (Jupyter), strategy (factor models + regime-based dynamic weighting), execution (automated reconciliation + risk controls), reporting (Power BI). AI-assisted development, human-in-the-loop on every model.

Result. Fully operational in 8 weeks. 100% daily position match. New strategy deployment in <1 week. 40% drawdown reduction during Q1 dislocations.

UTA
Utah Transit Authority
Fare Analyst, Project Engagement
Oct 2024 → Jan 2025

Fare-structure forecasting + vendor SLA accountability across a 250-machine fleet.

Two parallel work streams: (1) fare analytics and revenue forecasting with SQL, Python, and Power BI/Tableau; (2) vendor accountability analytics across the newly-installed 250+ TVM fleet — error-log analysis, field testing, and a scope accountability document that turned vendor-support failures into enforceable SLAs.

Key Accomplishments
  • Built dashboards tracking 20+ KPIs across 7 lines, cutting report-gen time from 8 hrs/wk to 15 min automated.
  • ARIMAX fare-structure forecast with elasticity incorporated — findings drove the exec decision to phase an 8% increase.
  • A/B test on student discount: 18% ridership uplift with 25% revenue-loss reduction via targeted eligibility.
  • Diagnosed the TVM vendor was filtering non-critical error classes at the source, leaving Control Center blind to machine outages.
  • Authored the scope accountability document used in vendor negotiations — line-by-line contracted scope vs. field error data; vendor agreed to fix pipeline and accept SLA enforcement.
Highlighted Story • Vendor Accountability
Turned a vendor-support failure into enforceable SLAs using data.

Situation. 250+ new TVMs across TRAX/FrontRunner/bus; machines were going down and the vendor wasn't surfacing error alerts to Control Center as contracted. UTA was losing revenue and rider trust blind.

Action. Three tracks in parallel: pulled raw vendor logs and cross-referenced to what Control Center actually received (class-by-class gap quantification), on-site field testing to reproduce outages, and a scope accountability document mapping contractual support scope line-by-line against observed field errors.

Result. Vendor agreed to fix the error-reporting pipeline and accepted ongoing SLA enforcement. Detection moved from rider-complaint-driven to near-real-time. The scope accountability doc became the standing reference for future vendor-support reviews.

WS
Website Squirrel
Director of Growth & Marketing Data Analytics
Apr 2023 → 2024

Lead scoring & behavioral segmentation that cut CAC 60%+.

Owned growth marketing and analytics for a fast-growing B2B SaaS. Built automated lead-scoring and customer-segmentation models in SQL across CRM, transactional, and behavioral data. Architected Python/AWS pipelines. Analyzed 48+ campaigns and 120+ competitors.

Key Accomplishments
  • Lead CAC down 60%+ via automated scoring + behavioral segmentation; top quintile converted at 28% vs. 8% company average.
  • Customer retention up 20% via automated win-back campaigns; 35% of at-risk customers recovered before renewal.
  • Automated Python/AWS pipelines eliminated 15 hrs/wk of manual reporting.
  • Contributed to 15% YoY profit growth through channel optimization and improved targeting.
  • ROI analysis across 48+ campaigns drove 22% improvement in marketing efficiency.
Highlighted Story
Predictive scoring turned a 40% churn problem into a growth lever.

Situation. 40% of new customers churning within 12 months; marketing spending equally on high-intent and low-intent segments.

Action. Pulled 2 years of CRM + transactional + behavioral data. Built logistic regression models for conversion probability and churn risk, deployed into HubSpot via API for automated scoring + triggered nurture tracks (accelerated sales for high-score, longer nurture for low-score, win-back 60 days pre-renewal for at-risk).

Result. 60%+ CAC reduction, 20% retention lift, time-to-nurture cut from 5+ days manual to <2 hrs automated. Combined: 22% marketing-efficiency gain, 15% contribution to YoY profit.

N
Netgain Solutions
Director, Marketing Operations & Analytics
Sep 2021 → Mar 2023

6-product portfolio, 30-touchpoint journeys, +250% mid-funnel lift.

Owned marketing ops analytics across a 6-product B2B SaaS portfolio with lead cycles from 1 to 18 months and 30 touchpoints per closed deal. Built multi-touch attribution, lead/user scoring, and cohort analysis. Isolated the "Moments that Matter" — the North Star Metric — and ran high-velocity testing sprints to drive more leads through them faster.

Key Accomplishments
  • 250% lift in PPC/SEO mid-funnel conversion (SQL-to-SAL) by isolating the NSM.
  • Built online + offline multi-touch attribution across 6 products and 1–18 month lead cycles.
  • Lead/user scoring assigned a dollar value to every click, view, form, event — real ROAS and CAC by channel.
  • Automated lead routing + scoring lifted sales productivity 15%.
  • Usage analysis across 20+ customer segments surfaced 8 expansion opportunities, drove 12% YoY NDR growth.
Highlighted Story
"Moments that Matter" — a single NSM across 6 products.

Situation. 6-product portfolio, 30-touchpoint average journey, mid-funnel SQL-to-SAL underperforming; budget split roughly equally with no dollar-value attribution back to source.

Action. Built multi-touch attribution + dollar-weighted scoring. Ran cohort analysis across 12 months of leads to surface the sequence that best predicted conversion: second product-page revisit + pricing-page touch + sales-collateral download in a 14-day window. Made NSM throughput the primary mid-funnel KPI. Ran high-velocity sprints to drive more leads through it faster.

Result. Mid-funnel conversion 8% → 20% (+250%). NSM throughput tripled. Low-intent spend reallocated; PPC contribution +18%. Combined impact directly influenced $4M+ pipeline growth in year 2.

F
Foxit eSign
Senior Marketing Director — Emerging Markets / Growth
Feb 2020 → Sep 2021

In-app lifecycle trigger engine + 72 hrs/week of reporting eliminated.

Ran Growth across a 4-product Foxit eSign portfolio. Built an in-app tracking + cohort segmentation system that targeted users for upsell/cross-sell based on actual product-usage patterns. Led a 6-person Growth team and 8-person cross-functional team unifying product, billing, support, and marketing data into one reconciled source of truth.

Key Accomplishments
  • In-app tracking + cohort segmentation across 4 products: frequency + duration + feature-mix signals drove upsell/cross-sell audiences.
  • Lifecycle trigger engine fired in-app messages, nurture emails, and sales/onboarding calls based on cohort — tested and scaled via high-velocity sprints.
  • Python reporting infrastructure eliminated 72 hrs/week of manual reporting (18 funnel + 25 billing reconciliation + 29 usage analysis).
  • Drove 3× ROI in a single quarter by scaling highest-LTV channels and highest-converting lifecycle triggers.
  • Executed 40+ growth experiments, scaled 12 high-impact initiatives, contributed to 28% YoY revenue growth.
> Highlighted Story
Unified data + lifecycle engine. 3× ROI in one quarter.

Situation. Growth, marketing, product, sales each looked at customer behavior through siloed systems. Upsell was manual and reactive. Cross-channel funnel analysis alone consumed 18 hrs/week.

Action. Two systems in parallel. (1) In-app tracking + cohort segmentation across 4 products, with triggered lifecycle actions promoted from high-velocity tests. (2) Python data layer reconciling product + billing + support + marketing into a unified customer dataset with LTV/CAC by channel. Two months of validation against manual reports before go-live.

Result. Lifecycle triggers became the biggest expansion lever on the team. 72 hrs/week of manual reporting eliminated. API partnership revealed as 3.2× LTV vs. self-serve, driving 3× partnership investment. 3× ROI in Q1 2021.

H
Healthicity
Digital Marketing Director & B2B Demand Gen Manager
Dec 2018 → Feb 2020

Doubled app conversion during rebrand launch.

Led consumer and B2B marketing during company rebrand. Managed demand gen for healthcare compliance SaaS. Doubled app conversion through analytics improvements. Grew social audience 400% in two months. Recruited and developed three team members.

Key Accomplishments
  • App conversion doubled (8% → 16%) by rebuilding product tracking, identifying friction, and optimizing mobile form flow.
  • Social audience 18K → 90K (+400%) in two months during rebrand launch.
  • Automated lead routing + scoring drove a 15% increase in qualified lead volume.
  • Nurture workflows cut time-to-first-touch from 4 days to <1 day; 22% conversion-velocity lift.
  • Recruited and developed 3 direct reports; established marketing processes for sustained growth.
Highlighted Story
Found the form-page-2 friction and doubled sign-ups before rebrand launch.

Situation. 8% sign-up conversion vs. 15–20% benchmark; no funnel visibility; rebrand launch 2 weeks out.

Action. Instrumented every step of the sign-up flow in GA + pixel tracking; identified 65% drop-off on form page 2 (license details). A/B tested form length, field clarity, and mobile experience in parallel.

Result. Conversion 8% → 16%. Form completion time 4 min → 2 min. Mobile conversion 4% → 12%. During rebrand launch the improvements delivered 40% more sign-ups from the same traffic, driving 3× ROI on rebrand investment.

TT
Tuff Toe, Inc.
Marketing Director — E-commerce Direct-to-Consumer
Sep 2015 → Oct 2018

ABM program grew B2B 68% YoY.

Led DTC and B2B marketing for premium footwear. Drove 68% YoY B2B growth via ABM + marketing automation. Achieved 62% ad-response uplift with 25% ACoS reduction. Grew organic traffic 20% YoY.

Key Accomplishments
  • B2B revenue +68% YoY through ABM and automated lead nurture across 150 target accounts.
  • 62% ad-response uplift with 25% ACoS reduction via audience segmentation and creative testing.
  • Organic traffic +20% YoY via content + technical SEO improvements.
  • Email program (welcome, cart abandonment, re-engagement) contributed 15% of online revenue.
  • Account avg deal size +35% through multi-stakeholder nurture identifying upsell earlier.
Highlighted Story
Reframed B2B as an ABM program, not a DTC sidecar.

Situation. B2B growing single digits while DTC was strong; no systematic way to target, nurture, or qualify B2B with 4–8 week cycles and multiple decision makers.

Action. Researched 4 buyer personas, identified 150 target accounts across corporate safety / industrial / healthcare. Vertical-specific landing pages, role-specific nurture (safety, procurement, compliance), 8-week multi-touch cadence, sales enablement (ROI calculators, battlecards).

Result. B2B revenue +68% YoY (vs. 8% baseline). Engagement 3× vs. broad B2B. Win rate +22%. B2B moved from 10% to 22% of company revenue.

R
RGM Group
Director of Marketing Analytics & Paid Media
Dec 2012 → Aug 2015

Multi-touch attribution across $50M+ in agency media spend.

Directed marketing analytics and paid media ops for full-service performance agency. Built attribution dashboards and KPI reporting for multi-million-dollar media budgets. Owned the marketing data intelligence function.

Key Accomplishments
  • Attribution dashboards for 8+ clients managing $50M+ in annual media spend.
  • Multi-touch model for B2B client with 8-week cycle improved budget allocation accuracy 18%, increased pipeline-contribution attribution 40%.
  • Cross-client analysis surfaced best practices applied to 6 client campaigns.
  • Self-service Excel/Tableau templates reduced time-to-reporting 60% for new clients.
Highlighted Story
Built the MTA model that reframed 70% of marketing ROI.

Situation. B2B SaaS client with 8-week cycle; last-touch attribution credited only the final touch, leaving the bulk of marketing spend undervalued.

Action. Analyzed 2 years of deal data, tracking every touch through close. Built a linear multi-touch model validated against time-decay and position-based alternatives, stress-tested for edge cases, delivered with 95% CIs and documented assumptions.

Result. Full-funnel marketing now credited with 70% of revenue impact (vs. 20% last-touch). Budget allocation +18%. Sales and marketing aligned on attribution credibility. Client expanded relationship into content marketing + ABM.

Education & Technical Stack

The toolkit.

Education

MBA
Pepperdine University • Graziadio School of Business
BS, Business
Argosy University
AS, Business
Utah Valley University
In Progress
Microsoft PL-300 (Power BI) • Google Data Analytics

Core Technical Skills

Languages

SQL Python DAX HTML/CSS

BI & Visualization

Power BI Tableau Looker Data Studio

Data Stack

pandas NumPy dbt AWS (S3, Lambda) BigQuery Airflow

Marketing & Business Tools

HubSpot Salesforce Google Ads Meta Ads LinkedIn Ads GA4 Mixpanel Amplitude SEMrush Ahrefs

Methodologies

Multi-touch Attribution A/B & MVT Testing Cohort Analysis ARIMAX Logistic Regression Elasticity Factor Models Regime Analysis