Growth Data Scientist - Build Production ML for Scale

Quince; Palo Alto, Northern (CA, KY); Hybrid; USD 171,000 - 198,000; Full time

Benefits offered by this job

Bonus & Equity

Job summary

Quince is seeking a Data Scientist, Growth to own machine-driven decision engines and automated bidding infrastructure across 40+ units. This role offers end-to-end model development, production systems, and direct exposure to executive leadership, driving measurable top- and bottom-line effects.

You will blend rigorous applied research with rapid technical execution, collaborating with marketing, product, and data science teams to optimize spend and performance at scale.

Qualifications

• 2+ years of technical experience, including at least 1 year in industry.
• Proven Python and SQL expertise with live production ML deployment.
• Strong analytical/problem-solving skills and independence.
• Excellent collaboration with marketing, product, and leadership.
• Ability to operate in a fast-paced, entrepreneurial environment.

Responsibilities

• Work on the core automated bidding infrastructure and allocation algorithms.
• Build end-to-end production ML models with high-visibility impact.
• Design, build, and productionalize autonomous models and data pipelines.
• Manage ad platform integrations and optimize marketing workflows.
• Work on automated processes for design and creative production.
• Dig deep into complex systems and tackle optimization problems.
• Collaborate cross-functionally with teams while maintaining executive visibility.

Skills

Python

SQL

Production ML

Analytical thinking

Cross-functional collaboration

Job description

Quince is seeking a Data Scientist, Growth to own machine-driven decision engines and automated bidding infrastructure across 40+ units. This role offers end-to-end model development, production systems, and direct exposure to executive leadership, driving measurable top- and bottom-line effects.

You will blend rigorous applied research with rapid technical execution, collaborating with marketing, product, and data science teams to optimize spend and performance at scale.