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.