Job Description

Job Description

SENIOR DATA SCIENTIST - SEARCH AND RECOMMENDATIONS

SAN FRANCISCO BAY AREA (HYBRID)

$160,000 – $190,000 BASE SALARY + EQUITY

ABOUT THE ROLE

We’re seeking a Data Scientist II to drive next-generation personalization and discovery for a fast-growing social commerce marketplace. You’ll partner with Machine Learning Engineers and product teams to design, build, and deploy models that impact millions of daily buyers and sellers. This is a high-impact, hands-on position ideal for someone passionate about transforming large-scale data into measurable business outcomes.

KEY RESPONSIBILITIES

• Model Development: Build and refine recommendation, personalization, and ranking models that scale to millions of users and hundreds of thousands of new listings each day.
• Experimentation: Design and analyze A/B tests, iterating on metrics such as click-through rate, conversion, and listing quality.
• Collaboration: Work closely with MLEs to move models from prototype to production, ensuring performance and reliability.
• Data & Insights: Explore large-scale marketplace data to identify trends, create features, and improve model accuracy.
• Cross-Functional Impact: Partner with product, engineering, and analytics stakeholders to translate business needs into technical solutions.

REQUIREMENTS

• 3+ years of applied data science or machine learning experience
• Proficient in Python and deep learning frameworks (PyTorch or TensorFlow)
• Hands-on with recommendation, ranking, or personalization models at consumer scale
• Skilled in working with high-volume data and deploying production ML systems
• Knowledge of full ML lifecycle: development through monitoring
• Familiar with modern data infrastructure (Databricks, Feature Stores) and cloud platforms (GCP/AWS)

Why Join

• You’ll join an expanding AI/ML team that’s scaling rapidly to support multiple product squads, offering opportunities to work on cutting-edge projects and deepen your technical expertise. Expect mentorship from senior staff scientists, visibility across teams, and the chance to shape personalized shopping experiences for millions of global users.

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