Staff Data Scientist at Poshmark in US California (Redwood City) - Office

Job description

• Application

Responsibilities

• Lead end-to-end data science initiatives, from ideation to deployment, delivering measurable business impact through projects such as feed personalization, product recommendation systems, computer vision and GenAI.
• Collaborate cross-functionally with ML engineers, product managers, and business stakeholders, to design and deploy high-impact models.
• Develop scalable solutions for key areas of product, marketing, operations, and community functions.
• Own the entire ML development lifecycle: data exploration, model development, deployment, and performance optimization.
• Explore and experiment with emerging AI trends, technologies, and methodologies to keep Poshmark at the cutting edge.

Requirements

• 5–8 years of experience building scalable data science solutions in a big data environment.
• Hands-on experience with key machine learning algorithms, including CNNs, Transformers, and Vision Transformers.
• Proficiency in Python, SQL, and Spark (Scala or PySpark), with experience in deep learning frameworks such as PyTorch or TensorFlow.
• Solid understanding of linear algebra, statistics, probability, calculus, and A/B testing concepts.
• Strong problem-solving skills and the ability to communicate complex technical ideas effectively to diverse audiences, including executives and engineers.
• Experience with personalization algorithms, recommendation systems, or user behavior modeling.
• Familiarity with Large Language Models (LLMs) and techniques such as Retrieval-Augmented Generation (RAG) or Parameter-Efficient Fine-Tuning (PEFT).

Skills

Required

• Python
• SQL
• Spark (Scala or PySpark)
• PyTorch or TensorFlow
• Linear algebra
• Statistics
• Probability
• Calculus
• A/B testing concepts

Preferred

• Personalization algorithms
• Recommendation systems
• User behavior modeling
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Parameter-Efficient Fine-Tuning (PEFT)

Benefits

• The base pay range listed for this position may span multiple levels of experience, and final compensation is determined by a variety of job-related factors, including relevant experience, demonstrated expertise, and internal equity.
• The posted range applies to base salary only and does not include additional elements of total compensation, which may include equity, performance-based incentives, and a comprehensive benefits package.