PayPal

Senior Data Scientist

PayPal

full-time

Posted on:

Origin:  • 🇺🇸 United States • California

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Salary

💰 $123,500 - $212,850 per year

Job Level

Senior

Tech Stack

AWSAzureBigQueryCloudDistributed SystemsETLGoogle Cloud PlatformJavaPythonPyTorchTensorflow

About the role

  • Design, develop, and deploy machine learning models using GCP services such as AI Platform, BigQuery ML, Vertex AI, TensorFlow, and AutoML.
  • Build and optimize scalable pipelines for data collection, preprocessing, and feature engineering.
  • Collaborate with data engineers to design ETL pipelines and manage large datasets on GCP.
  • Develop custom machine learning models tailored to business needs, including supervised, unsupervised, and reinforcement learning algorithms.
  • Integrate AI/ML models into cloud applications and ensure seamless operation in production environments.
  • Work closely with software engineers to embed AI/ML models into applications and products, ensuring best practices for CI/CD in ML.
  • Conduct research to stay up-to-date with the latest AI/ML techniques and apply them to business use cases.
  • Perform model tuning, evaluation, and monitoring for performance and accuracy improvements.
  • Provide mentorship and guidance to junior developers and contribute to code reviews, technical design sessions, and project planning.
  • Ensure security, scalability, and performance of ML models deployed in production.

Requirements

  • Minimum of 5 years of relevant work experience
  • Bachelor's degree or equivalent experience
  • Master's degree or higher preferred in Computer Science, Mathematics, or related field
  • Proven experience in developing and implementing solutions in machine learning and AI-related spaces
  • Strong programming skills in languages such as Python, Java, or C++
  • In-depth knowledge of machine learning frameworks and libraries for analytics and text processing (e.g., TensorFlow, PyTorch)
  • Experience with cloud services related to machine learning (Vertex AI, etc.)
  • Experience integrating ML solutions into cloud environments (e.g., AWS, Azure, GCP) is highly desirable
  • Strong knowledge of algorithms, statistics, data structures, distributed systems, and software engineering best practices
  • Excellent problem-solving skills
  • Strong communication skills
  • Proven experience leading and delivering complex ML projects at production scale