Machine Learning Engineer 2

$140,000 - $204,600/Yr

Braintree - San Jose, CA

Full-time - Mid Level

Remote - San Jose, CA

Personal and Laundry Services

About the position

The Machine Learning Engineer 2 at PayPal is responsible for developing and validating advanced data mining tools and algorithms to address business challenges. This role involves collaborating with research scientists and engineers to implement innovative data mining techniques, working with large datasets, and communicating complex analyses effectively. The engineer will also write high-quality code for data processing related to payment systems and develop novel techniques to ensure data quality and security.

Responsibilities

• Develop and validate advanced data mining tools and algorithms to solve business problems.
• Collaborate with research scientists and engineers to formulate innovative solutions and implement advanced data mining techniques.
• Work with large volumes of data and manipulate datasets using tools such as Python, Hadoop, R, and SQL.
• Analyze data from user profiles to transaction histories to identify new risk patterns.
• Communicate complex concepts and analysis results through creative visualization.
• Write clean, high-performance, maintainable code for data processing related to payment systems.
• Develop novel data mining techniques and algorithms to ensure data quality and secure storage.

Requirements

• Master's degree in Statistics, Data Science, or a closely related field.
• One year of experience in the job offered or a related occupation.
• Experience in machine learning, recommendation systems, pattern recognition, and data mining.
• Proficiency in developing machine learning models at scale from inception to business impact.
• Experience in predictive analytics and developing scalable classifiers and tools using machine learning and data regression.
• Strong background in statistics, data science, data analysis, and data cleaning.
• Proficiency in Python data engineering and adapting machine learning methods for modern parallel environments.
• Knowledge of data structures and algorithms.

Benefits

• Flexible work environment
• Employee stock options
• Health insurance
• Life insurance
• Mental health resources