Data Scientist, Seller Merchant — Remote & High-Impact

Whatnot; New York (NY); Hybrid; USD 120.000 - 180.000; Vollzeit

Benefits dieser Stelle

Health Insurance

Work From Home Support

Parental Leave

401k with employer match

Zusammenfassung

Whatnot in New York is seeking a Data Scientist for the Seller Merchant team. You’ll use data to understand differences among sellers, design experiments, and influence product decisions that improve activation, inventory creation, and GMV.

You should have 5+ years in product data science, strong SQL and Python skills, and experience with experimentation, causal inference, and Bayesian methods. Collaboration with product and engineering is essential to drive impact.

Qualifikationen

• Bachelor's degree in Statistics, Economics, Computer Science, Mathematics, or related quantitative field.
• Strong product and business judgment with the ability to translate questions into analyses and recommendations.
• Deep knowledge of experimentation, causal inference, and statistical methods, including Bayesian approaches for small/ noisier data sets.
• Strong statistical judgment about what the data can support and when to involve product/business judgment.
• Advanced SQL and working proficiency in Python; comfortable using code for analysis and evaluation.

Aufgaben

• Identify and prioritize high-impact opportunities to improve seller success and GMV.
• Design and evaluate experiments across the seller experience with cross-functional partners.
• Develop analytical frameworks to shape product strategy beyond ad-hoc questions.
• Analyze differences across seller segments and determine when to tailor experiences.
• Apply analytics and inference when data is imperfect, guiding product decisions with evidence.

Kenntnisse

SQL

Python

Experimentation

Causal Inference

Statistics

Cross-functional

Bayesian Methods

Ausbildung

Bachelor's degree in Statistics or related field

Tools

SQL

Python

Jobbeschreibung

Whatnot in New York is seeking a Data Scientist for the Seller Merchant team. You’ll use data to understand differences among sellers, design experiments, and influence product decisions that improve activation, inventory creation, and GMV.

You should have 5+ years in product data science, strong SQL and Python skills, and experience with experimentation, causal inference, and Bayesian methods. Collaboration with product and engineering is essential to drive impact.