Data Science · Analytics · Live Pipelines
End-to-end data projects with live pipelines. From raw data to actionable predictions across finance, healthcare, marketing, and supply chain.
About
Data scientist and analytics engineer focused on end-to-end pipelines that stay live. Every project on this site pulls fresh data, runs automated transformations, and delivers actionable outputs. The work spans finance, healthcare, SaaS marketing, and supply chain logistics.
Projects
Each industry has two connected projects: an analytics layer that discovers the pattern, and a data science layer that predicts what happens next.
When a tariff hits, who makes money and who bleeds, by how much, and with what lag?
Sector ETF returns mapped to tariff announcements. Quantified P&L impact with first, second, and third-order effects across the supply chain dependency graph.
Can we systematically profit from tariff announcements using sector pair trades?
Predictive model for post-announcement sector divergence. Backtested long/short strategies with Sharpe ratio and alpha vs. benchmark for each tariff event.
Which drugs are one disruption away from critical shortage, and why?
200+ active shortages mapped to geographic supply chain bottlenecks and single-source manufacturer risk. Concentration analysis across production facilities.
Can we predict which drugs will enter shortage in the next 90 days?
Manufacturer HHI concentration scores, geographic risk indices, FDA inspection failure rates, and tariff exposure signals combined into a survival analysis model.
Which SaaS companies get the best ROI on their marketing dollar, and who is burning cash?
S&M spend as percentage of revenue from SEC 10-Q filings for 50+ public SaaS companies, overlaid with Google Trends brand interest and Reddit sentiment. CAC efficiency benchmarks.
When brand sentiment shifts, how long until it shows up in revenue, and by how much?
Predict next-quarter revenue growth from marketing spend trends, Google Trends momentum, and Reddit sentiment velocity. Granger causality testing and lag modeling.
Which shipping lanes and product categories are under stress right now?
Real-time composite of container freight rates (FBX), port congestion metrics at 100+ ports, route-level delays, and downstream retail inventory signals.
Which retail categories will face stockouts in the next 30-60 days?
Leading indicators: port congestion trends, freight rate spikes, vessel re-routing, and weather events. Predicts category-level delays before they reach shelves.
Writing
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Contact
Interested in working together or discussing data projects. Available for full-time roles, contract work, and consulting.
Thursday & Friday 12:00 - 1:00 PM EST · Saturday 10:00 AM - 1:00 PM EST
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