Data Scientist: Matching, Forecasting & Pricing for Marketplace

Farmchefconnect; Houston (TX); On-site; USD 95,000 - 116,000; Full time

Benefits offered by this job

105,000 USD base salary

Two seats to build modeling practice

Models deployed to live marketplace

Growth path and SOP from day one

Job summary

VK Capital Ventures Inc. is hiring two Data Scientists for Travel Villa Kitchen and related ventures in Houston. The role focuses on matching, forecasting, and pricing models using household, market, and platform data.

Responsibilities include building a vendor and demand forecasting pipeline, and presenting results to founders in plain language. Requires strong Python/R, SQL, and experience with small-n data in real-world settings.

Qualifications

• Degree in statistics, math, computer science, or equivalent experience (master's preferred)
• Proficiency: Python/R + SQL
• Experience with messy, small-n real-world data
• Comfort presenting findings to non-technical audiences
• Nice to have: geospatial/ZIP-level work, survey data, marketplace experience
• Bilingual English/Spanish a plus

Responsibilities

• Build Protein Pool matching model v1: households → nearest rancher by ZIP with allocation math
• Build the demand forecast for demos, classes, and dinners in the Data Science OS weekly snapshot
• Build placement-matching scoring for the chef placement engine to shortlist
• Co-own the written data-quality audit with analytics team
• Present findings to non-technical founders and community partners in plain language

Skills

Python/R

SQL fluency

Small-n data experience

Present findings to non-technical

Geospatial/ZIP-level work

English/Spanish bilingual

Education

Statistics/Math/CS degree

Job description

VK Capital Ventures Inc. is hiring two Data Scientists for Travel Villa Kitchen and related ventures in Houston. The role focuses on matching, forecasting, and pricing models using household, market, and platform data.

Responsibilities include building a vendor and demand forecasting pipeline, and presenting results to founders in plain language. Requires strong Python/R, SQL, and experience with small-n data in real-world settings.