Machine Learning Engineer 2

$140,000 - $204,600/Yr

PayPal - San Jose, CA

Full-time - Mid Level

Remote - San Jose, CA

Credit Intermediation and Related Activities

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 data insights effectively. The engineer will also write high-quality code for data processing related to payment systems and develop novel algorithms 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; extract and manipulate datasets using tools such as Python, Hadoop, R, and SQL.
• Analyze data covering a wide range of information from user profiles to transaction history.
• Identify new risk patterns through data mining.
• Communicate complex concepts and 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 plus 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 statistical and data analysis skills.
• Experience in data cleaning and Python data engineering.
• Knowledge of adapting standard machine learning methods for modern parallel environments.

Nice-to-haves

• Experience with distributed clusters, multicore SMP, and GPU environments.
• Familiarity with data structures and algorithms.

Benefits

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