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.

Job Tags

Similar Jobs