Max Krehbiel
I'm in the M.S. in Business Analytics program at TCU's Neeley School of Business, graduating in May 2027. These are tools I've built for deal sourcing, options research, storm response and land management, each rebuilt here with made-up or public data so the code can be shared.
Resume (PDF) maxkrehbiel@gmail.com LinkedIn (opens in a new tab) GitHub (opens in a new tab)
Projects
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Thesis to Target
Most buy-side firms source deals from the same few databases, so the same companies get called by every buyer. I built a tool that pulls company records from licenses, registries and directories, merges the duplicates into companies, and estimates the probability that each company's EBITDA falls in the buyer's range.
It also checks whether each company already shows up in the big databases, which tells a buyer where other firms probably aren't looking. Every number in the output links back to the record it came from.
First built for a buy-side M&A origination firm. This version runs on made-up companies.
Python · entity resolution · probability modeling
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Storm Lead Engine
After a hailstorm, the useful question isn't where it hailed. It's which roofs took enough hail to be worth an inspection. This reads NOAA's radar hail estimates, maps where 1, 1.5 and 2 inch hail fell, and records the hail each property has taken since its current roof went on.
Each property gets a score where every point is visible, and contractors are ranked so a 5.0 from three reviews doesn't beat a 4.8 from four hundred.
First built for a roofing client. This version uses a made-up storm season and town.
Python · NOAA radar data · Bayesian scoring · GeoJSON
Read the case study Open the live map (opens in a new tab) Code (opens in a new tab)
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Camera Trap Pipeline
Our trail cameras on Heart 7 took about 13,000 photos. A lot of them are empty, and one deer walking past shows up as a burst of several frames. I built a pipeline that sets the empty photos aside, isolates each animal in its own box and identifies the species from that crop.
Photos from the same visit are grouped, so one deer counts once, not once per photo. It also flags camera problems, like a clock that reset when the batteries died or a camera that went dark for days, and it saves its progress after every step so a crashed run picks up where it stopped.
The public version runs on drawn, synthetic photos with the same field problems planted in them.
Python · MegaDetector · SpeciesNet · Parquet
Read the case study Open the live report (opens in a new tab) Code (opens in a new tab)
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Options Density Lab
Option prices hold the market's own odds for where a price will end up. This recovers that probability distribution from a chain of option quotes: it cleans the quotes, fits a smooth volatility smile that rules out arbitrage, and reads the distribution off with the Breeden-Litzenberger identity.
Every quote comes from a model whose true distribution is known, so each step can be graded against the right answer. Across 10 test chains, the recovered distribution's median error is between 0.8% and 1.9%.
A public version of one building block of my OpenK research, run on synthetic quotes.
Python · options · numerical methods · model validation
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LiDAR Terrain Lab
Before a cedar-removal job on Heart 7, I needed two answers: how many acres the brush and young trees had taken over, and where water goes when it rains. Airborne LiDAR answers both, because every laser return records the height of whatever it hit.
This separates ground returns from vegetation, builds bare-earth and canopy-height models on a 1 meter grid, routes water across the terrain to find drainage lines, and totals acreage by vegetation height and by management zone.
Grew out of scoping a $130K cedar-removal program on Heart 7 Ranch. The demo runs on a synthetic landscape; real runs use public USGS data.
Python · LiDAR · raster analysis · hydrology
Read the case study Open the live report (opens in a new tab) Code (opens in a new tab)
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OpenK Research Site
OpenK is my independent research on the shape of market uncertainty: the range of outcomes prices imply, not a single forecast. This is the website that publishes it.
Every page is prerendered, the charts are hand-written SVG and Canvas with no charting library, and the only code that runs per request is a contact form and a newsletter signup with strict input checks.
TypeScript · Next.js · data visualization
Read the case study Visit openkresearch.com (opens in a new tab) Code (opens in a new tab)
Experience
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May 2023 – Present
OpenK Investments – Lead Researcher
Quantitative Researcher, Fort Worth, TX
- Tested whether investor overreaction during periods of market stress created persistent option mispricing, identifying historically profitable trading opportunities and recurring deviations from market-implied expectations.
- Built and validated a 97-million-record options fact base spanning 13 years, with near-complete trading-day coverage, rigorous quality controls, and standardized data structures for large-scale empirical testing.
- Redesigned a 90+ TB modeling architecture to cut calibration from 18 hours to 45 minutes, improve probability accuracy by ~5%, and enable wider parameter-grid and robustness testing at scale; none of 40 randomized falsification trials reproduced the result.
- Rejected a 24% CAGR strategy after robustness tests showed excessive dependence on market regime and timing.
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December 2025 – Present
Cross City Connection – Founder
Strategy & Analytics Consultant, Fort Worth, TX
- Advised an owner choosing between two oil and gas businesses on profitability, market size across ~2,100 Texas facilities, execution risk, and capital; the owner exited $1M+ construction for a $3M+ compliance business.
- For a buy-side M&A origination firm, resolved 121,000 records into ~110,000 companies, estimated EBITDA, and ranked 867 targets above $1M EBITDA; 648 (75%) had no PitchBook or Crunchbase profile.
- Routed a roofing client’s canvassers to older roofs on high-value homes using storm and permit data.
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June 2024 – August 2025
100 Year Homes – Analyst
Real Estate Portfolio Analyst and Operations Manager, Omaha, NE
- Analyzed rate, repair-cost, rent, and operating sensitivities across 350 properties and recommended whether to renovate, hold, or sell individual assets, supporting an ~$8M divestiture and broader capital allocation.
- Owned daily resource allocation for 12 workers and 4 trucks across 5–7 concurrent projects, translating owner priorities and changing site conditions into staffing decisions that improved operational efficiency.
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June 2024 – Present
Heart 7 Ranch
Ranch Manager – Finance & Operations, Johnstown, NE
- Manage an 815-acre ranch acquired for $1.6M, preparing full annual financial statements, depreciation schedules, tax filings, and operating budgets while directing day-to-day operations and capital decisions.
- Built debt and operating pro formas for bison and wing-shooting ventures; deferred a $230K+ pre-livestock bison investment when projected cash flow did not justify the capital and downside risk across conservative debt, revenue, and cost assumptions.
- Negotiated and managed $300K+ in capital projects, using LiDAR, GeoTIFF, and field surveys to scope a $130K cedar-removal program while coordinating contractors, budgets, grant funding, and execution.
Leadership
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August 2026 – Present
Neeley AI Leadership
Chief Technology Officer, Fort Worth, TX
- Lead technical strategy for AI curriculum, investment-bank pitches, external partnerships, and an AI-focused investment fund while advising leadership on feasibility, standards, and organizational risk in case competitions and organization-wide initiatives.
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August 2024 – August 2026
Delta Tau Delta Fraternity
Professional Development Coach, Fort Worth, TX
- Expanded and standardized professional development for a 130-member chapter, establishing recurring elevator-pitch, career-fair, and recruiting programs while personally coaching 30 new members through 1:1 career development.
Education
Texas Christian University, Neeley School of Business
- Master of Science in Business Analytics, 4.0 GPAMay 2027
- Bachelor of Business Administration, Finance & Real Estate; Minor in Accounting, 3.99 GPAMay 2026
Neeley Senior Finance Scholar, Summa Cum Laude, TCU Scholar, Dean’s List (All Semesters)
Applied Finance Project: Merrimac Circle Phase II Development
- Built and presented a full pro forma for a 3.2-acre Phase II development directly to the developer, modeling $102M–$105M of costs, senior and mezzanine debt, DSCR, IRR, equity waterfalls, and interest- and cap-rate sensitivities under downside scenarios.
- Rejected a 140-room hotel in favor of a 205-unit mixed-use multifamily concept after hotel cash flow failed to support comparable debt or returns; the developer retained multifamily in its 295-unit plan and adopted elements of the recommendation.
Skills
- Skills
- Financial Modeling, Valuation, Due Diligence, Scenario Analysis, Capital Allocation, Strategy & Operations, Business Case Development, Process Design & Improvement, Data Analysis, Machine Learning, SQL, Python, Excel
- Applied AI
- 10B+ tokens and 43,000+ agent actions in Claude Code (Jun–Oct 2026); ~17,000 prompts since 2023
- Certifications
- Microsoft Office: Excel and PowerPoint
- Interests
- Wildlife Conservation, Classical Guitar, Motorcycle Mechanics, TCU Division 1-A Rugby, Slalom Skiing