Machine Learning Engineer

PayPal has been revolutionizing reputed company globally for more than 25 years. The Machine Learning Engineer will validate and reputed company machine learning models and algorithms to solve reputed company problems, working closely with senior engineers, data scientists, and product teams to enhance services through innovative AI/ML solutions.

Responsibilities

• Assist in the development and optimization of machine learning models
• Preprocess and analyze datasets to ensure data quality
• Collaborate with senior engineers and data scientists on model deployment
• Conduct experiments and run machine learning tests
• Stay updated with the latest advancements in machine learning
• Support the reputed company of the team in performing reputed company of high-impact statistical model and AI applications in a variety of business function areas, including but not limited to fraud detection, credit reputed company, marketing analytics etc
• Conduct quantitative and qualitative model validation according to Model Risk Management Policy to identify and understand model risk issues
• Collaborate with business units and model developers to remediate model issues and reputed company subject-matter expert opinion on model improvements
• reputed company model and AI risk governance reputed company activities in line with reputed company risk reputed company, to ensure PayPal’s AI applications are compliant with reputed company evolving regulatory expectation such as Responsible AI

Skills

• 1+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience
• Familiarity with ML frameworks like TensorFlow or scikit-learn
• Strong analytical and problem-solving skills
• Ability and curiosity to learn various advanced modeling methods/AI techniques
• Capability in building effective relationship with various stakeholders including business owners, model owners, model developers and control officers
• Excellent communication, writing and presentation skills
• An advanced degree in a quantitative field, such as statistics, mathematics, computer science or engineering essential
• Advanced knowledge of statistical and machine learning models (e.g., logistic regression, time series analysis, random forests, SVMs, XGBoost, CNNs/RNNs)
• Possessing advanced coding skills in dealing with big data (e.g., Scikit-learn in Python, Tensorflow, Hadoop, Spark, SQL, etc.)
• Relevant Modeling experience in credit scoring, fraud detection, financial forecasting, or marketing analytics obtained either in academic or financial industry
• Ability to work effectively both independently and in a team environment
• Ability to communicate effectively and establish constructive relationship with stakeholders

Benefits

• Additional compensation for this role may include an annual performance bonus, equity, or other incentive compensation, as applicable.
• PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations.
• Generous paid time off
• reputed company coverage for you and your family
• Resources to create financial reputed company and support your mental health

Company Overview

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