Residential real estate data and software tools for:- Private lenders- Fix-and-flip investors- SFR portfolio operators- Public equity investors & equity research (iBuyers, SFR REITs)- Various services businesses (property management, HVAC, etc)https://www.sfranalytics.com/

The fastest way for finance teams to do their work. Create workflows that are directly connected to live data sources, like bank accounts and accounting systems, to automate operations and reporting.

- Built the data infrastructure and processing (Python/SQL) to support multi-touch marketing attribution across advertising channels spanning digital and offline; attribution model used to drive $XMs in marketing spend annually in response to downstream performance metrics (return on ad spend, cost per contract, etc.)- Produced all analytical materials for $16M Series A, $36M Series B, $80M Series C, quarterly board meetings, etc.- Hired and led analytics team- Built the return and cash flow projection model (Python) used to guide decision making for a $20M+ real estate investment vehicle, including capital calls, cash-out refi recommendations, and scenario analysis- Built market sizing and competitive intelligence tools on top of 100s of GBs of transaction-level data. Used as an input to deciding which markets to enter, evaluate ongoing performance within markets, source property investors for the demand-side of the marketplace+ more...

SF office of a $1bn+ European family office

Modeling, reading debt covenants, etc

Commodities hedge fund that managed ~$1B at its peak.Worked with a proprietary dataset gathered by sensors embedded in natural gas pipelines throughout the United States to build dashboards and predictive models for the US natural gas market with a focus on basis differential trades.Modeled various aspects of energy consumption in the US & Europe; in particular, I developed a power generation stack model to estimate the source and cost of the marginal unit of capacity for countries in Europe.