Work samples focused on practical operating systems across growth, analytics, and automation, including current builds in intelligence pipelines, prospecting workflows, and translation automation.
Medisca · Ongoing initiative
Competitive Intelligence
Owned full implementation lifecycle (build, test, operate) for an event-based competitive intelligence pipeline.
Problem
Competitive updates were shared manually by the commercial team, creating inconsistent visibility across the organization.
Technical approach
Built event-based website scraping to monitor public competitor content and launch signals.
Used LLM analysis to convert raw page changes into decision-ready summaries.
Generated alerts, summaries, and brief-style email updates for go-to-market teams.
Published outputs into an internal app so Sales, Product, and Marketing can access current intelligence.
Stack & systems
Python
Firecrawl
Claude
Outcomes
Reduced missed competitive updates across Sales, Product, and Marketing.
Improved commercial alignment through shared event-based intelligence outputs.
Medisca · Ongoing initiative
Sales Prospecting Pipeline
Built a prospecting flow that automates list generation, enrichment, and alerts for Sales coverage.
Problem
Outreach and list building were manual and inconsistent across territories.
Technical approach
Built a Python-based flow that pulls licensing and business-source data to identify potential clients.
Used MedPro and Google Business Profile as core prospecting signal sources.
Detected newly registered license holders and surfaced them as sales-ready opportunities.
Generated prospect lists, alert updates, and enrichment outputs for territory-level outreach.
Distributed outputs through recurring email briefs and operational list exports.
Stack & systems
Python
Claude
Outcomes
Improved sales efficiency by reducing manual list-building effort.
Supported new-account growth by surfacing net-new opportunities faster.
Built and implemented an end-to-end SharePoint automation flow where users upload files and receive reviewed translations in a target-language return folder.
Problem
Manual translation took around five days: documents were sent to a platform, quoted, accepted, and then queued for delivery.
Technical approach
Triggered translation jobs directly from file uploads in a SharePoint upload folder.
Automated translation processing with DeepL through Power Automate while preserving formatting and styling.
Applied glossary and consistency controls so translated outputs stay aligned with channel language standards.
Routed translated drafts to the channel owner for QA and approval, then returned approved files to a separate folder.
Stack & systems
SharePoint
Power Automate
DeepL
Outcomes
Increased design-team throughput by 40%.
Increased communications-team throughput by 20%.
Delivered over $500K in savings in the first year.
Medisca · Ongoing optimization initiative
Product Recommendation Model
Owned full end-to-end delivery: requirements, solution design, implementation, and ongoing optimization.
Problem
Product discovery was low on the website experience.
Technical approach
Implemented recommendation modules directly on product detail pages.
Used add-to-cart and purchase behaviors as core recommendation inputs.
Returned product recommendations to increase discovery depth for active shoppers.
Measured and optimized performance using GA4 attribution modeling.
Stack & systems
Algolia
GA4
Outcomes
Drove over $1M in revenue impact through recommendation-led product discovery.