Experience

Experience

I have worked in analytics since 2017 across digital health, marketing, retail supply chain, logistics, and sales. Current work sits in decision science, growth, and data systems.

I own marketing attribution and measurement at Lark Health. My work covers acquisition, enrollment, lifecycle channels, paid media, direct mail, activation, and partner programs.

Attribution and channel measurement

I rebuilt production acquisition attribution after the existing system had accumulated independent first-match classifiers, hard-coded rules, and incomplete tracking. Around March 2026, on a trailing 365-day view, about 42% of enrollments were unresolved. The rebuilt model reduced unknown attribution to about 8%.

For one partner population in Q4 2025, direct mail’s measured share of enrollments moved from about 4% under the previous measurement to about 38% after corrected attribution. Direct mail had been scheduled for retirement. The corrected measurement changed the evidence used to evaluate the channel, and it stayed in use. This is a measurement correction, not an incrementality result.

Lifecycle and engagement systems

I built production Snowflake and dbt models connecting attribution and Braze email, SMS, and push activity to downstream behavior and program milestones. During the migration, I found and corrected legacy logic, source, identity, and downstream measurement issues.

MDPP/D2C measurement architecture

For Lark’s Medicare DPP launch, I defined Marketing’s measurement path from paid source and campaign through enrollment, eligibility, account creation, activation, engagement, and billable milestones. I also built a downside, base, and upside planning model that shows CAC per account, cost per first billable event, likely funnel losses, and the assumptions that matter most.

Decision and experiment readiness

For Samsung partnership measurement, I defined experiment-ready requirements that separate assignment from actual exposure and support ITT analysis, SRM checks, power planning, guardrails, and explicit decision rules.

I worked on marketing planning, web performance, attribution, and the data environment behind executive reporting.

Executive resource decision

On a three-hour deadline, I built a media-contribution model and recommended a $6.9M Q4 marketing budget against an outside proposal of about $11M from an external analytics consultancy. The analysis shaped CEO and CMO planning.

Root-cause analysis

I led analysis of a 42% year-over-year decline in web traffic. The work identified a 40% to 75% deterioration in CTR or message resonance, depending on the comparison, as an important driver. I presented the findings and implications to VP leadership.

Data architecture

I designed a Databricks-centered marketing-data environment integrating more than five sources, improved Adobe Analytics reporting, established UTM and attribution governance, and reduced manual reporting by at least 35%.

Methods and analyst development

I prototyped the company’s first internal Marketing Mix Model using Google Meridian. I also selected and recommended a junior analyst candidate, then led his onboarding and analytical development.

I supported nationwide supply-chain programs through SQL validation, execution measurement, and reporting automation.

Nationwide stock rebalance

I developed SQL-based validation and fulfillment measurement for a stock-rebalance program spanning thousands of SKUs and, at times, about 40% of stores. The program reached about 93% fulfillment and shipping success.

Forecasting support and automation

I automated Alteryx pipelines feeding executive Power BI reporting, eliminating about 20 hours of manual work per week. I also contributed data inputs, contracts, and input-selection decisions to a Python demand-forecasting initiative that reduced clearance items by about 7% network-wide.

I provided pro bono Python and SQL analytics and requirements support for small-business and independent projects involving e-commerce customers, sales reporting, lightweight analytical models, and business strategy.

I combined commercial freight pricing, sales enablement, and building the first analytics function inside an asset-light 3PL during the post-COVID freight market.

Commercial pricing

I priced competitive freight bids for customers including Nestlé and BODYARMOR using market rates, lane history, prior coverage, carrier capacity, serviceability, margin, customer requirements, and changing market conditions. Pricing had to win business while remaining profitable and operationally deliverable.

Pricing workflow and measurable adoption

I designed a HubSpot field pricing-request workflow and data contract, built video and hands-on training, and drove adoption. Response time improved about 43% and win rate improved about 22%. The work contributed to a period of about 26% annual company revenue growth.

Analytics leadership

I helped establish the company’s first analytics function and data stack, directly managed and developed one analyst, and trained another team lead.

This is where I started in people leadership, customer behavior, pricing, marketing, and commercial execution.

People and operational leadership

I directly managed up to five salespeople and coordinated four to ten additional shipboard personnel for major event logistics.

Commercial ownership

I managed pricing, marketing, sales strategy, customer experience, international inventory movement, and three to five auctions per week for multimillion-dollar onboard art collections. The teams regularly exceeded sales targets by about 20 to 80%.

Lark Health