Machine Learning Engineer
Role details
Job location
Tech stack
Job description
This job will validate and develop machine learning models and algorithms to solve complex problems. You will work closely with senior engineers, data scientists, and product teams to enhance services through innovative AI/ML solutions. Your role will involve building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences., * 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 lead of the team in performing oversight of high-impact statistical model and AI applications in a variety of business function areas, including but not limited to fraud detection, credit underwriting, 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 provide subject-matter expert opinion on model improvements
- Perform model and AI risk governance related activities in line with enterprise risk framework, to ensure PayPal's AI applications are compliant with ever evolving regulatory expectation such as Responsible AI., The base pay for this role will depend on where you work and the relevant experience and expertise you bring. The expected range of pay for this role by location is
Requirements
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1+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience.
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Familiarity with ML frameworks like TensorFlow or scikit-learn.
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Strong analytical and problem-solving skills., This position requires the ability and curiosity to learn various advanced modeling methods/AI techniques, covering a broader business function. This role also requires candidate to have the capability in building effective relationship with various stakeholders including business owners, model owners, model developers and control officers. The candidate must possess excellent communication, writing and presentation skills.
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An advanced degree in a quantitative field, such as statistics, mathematics, computer science or engineering essential
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Advanced knowledge of statistical and machine learning models (e.g., logistic regression, time series analysis, random forests, SVMs, XGBoost, CNNs/RNNs)
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Possessing advanced coding skills in dealing with big data (e.g., Scikit-learn in Python, Tensorflow, Hadoop, Spark , SQL, etc.)
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Relevant Modeling experience in credit scoring, fraud detection, financial forecasting, or marketing analytics obtained either in academic or financial industry
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Ability to work effectively both independently and in a team environment
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Ability to communicate effectively and establish constructive relationship with stakeholders
Benefits & conditions
Chicago, Illinois | ($117,500.00 - $174,350.00 Annually)
Additional Location(s) | Pay Range:
Austin, Texas | ($117,500.00 - $174,350.00 Annually)
Additional compensation for this role may include an annual performance bonus, equity, or other incentive compensation, as applicable.
PayPal does not charge candidates any fees for courses, applications, resume reviews, interviews, background checks, or onboarding. When making an application directly, we will never ask you to share passwords, one-time passcodes (OTP), or verification codes. Any such request is a red flag and likely part of a scam. All communication regarding your application will come from official PayPal email domains. If you suspect fraudulent activity, please report it immediately. To learn more about how to identify and avoid recruitment fraud please visit https://careers.pypl.com/contact-us.
For the majority of employees, 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.
Our Benefits:
At PayPal, we're committed to building an equitable and inclusive global economy. And we can't do this without our most important asset-you. That's why we offer comprehensive, choice-based programs, to support all aspects of personal wellbeing-physical, emotional, and financial-delivering meaningful value where it matters most.We strive to create a flexible, balanced work culture with a holistic approach to benefits, including generous paid time off, healthcare coverage for you and your family, and resources to create financial security and support your mental health.