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ZipRecruiter

Data Scientist

ZipRecruiter, San Mateo, California, United States, 94409

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DATA SCIENTIST II 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- 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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