Staff Data Scientist

US California (Redwood City) - Officefull timeOn Site

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senior

$0k–$0k

H1B: yes

Poshmark Staff Data Scientist leads end-to-end data science projects including personalization, recommendation systems, and AI innovations. Collaborates cross-functionally to develop scalable machine learning solutions impacting product, marketing, and community functions.

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.
Must-Have Qualifications:
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.

Qualification

Hands-on experience with CNNsProficiency in PythonSolid understanding of linear algebra6-Month Accomplishments12+ Month Accomplishments

Required

5–8 years experience building scalable data science solutions in big data environments
Hands-on experience with CNNs, Transformers, and Vision Transformers
Proficiency in Python, SQL, and Spark (Scala or PySpark)
Experience with deep learning frameworks such as PyTorch or TensorFlow
Solid understanding of linear algebra, statistics, probability, calculus, and A/B testing

Preferred

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).
6-Month Accomplishments:
Develop comprehensive understanding of Poshmark's data platform and key datasets.
Gained insights into challenges related to data scale and noise, implementing strategies to effectively leverage data in decision-making processes.
Demonstrated proficiency in Poshmark's machine learning systems by applying advanced algorithms to address a business use case.
Successfully prototype/enhance models aimed at improving key business metrics, contributing to data-driven solutions that support company objectives
12+ Month Accomplishments: