Job Summary
This job will design, develop, and implement machine learning models and algorithms to solve complex problems. You will work closely with data scientists, software engineers, 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. Experie
Job Description
Essential Responsibilities
- Develop and optimize machine learning models for various applications.
- Preprocess and analyze large datasets to extract meaningful insights.
- Deploy ML solutions into production environments using appropriate tools and frameworks.
- Collaborate with cross-functional teams to integrate ML models into products and services.
- Monitor and evaluate the performance of deployed models.
Expected Qualifications
- 3+ years relevant experience and a Bachelor s degree OR Any equivalent combination of education and experience.
- Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
- Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
- Several years of experience in designing, implementing, and deploying machine learning models.
Additional Responsibilities & Preferred Qualifications
Responsibilities
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Design, develop, and operationalize scalable machine learning and credit risk models, leveraging PySpark and advanced modeling frameworks.
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Build, train, and optimize statistical and deep learning models focused on credit scoring, fraud detection, and portfolio risk management.
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Collaborate cross-functionally with credit risk analysts, data engineers, and business teams to translate analytical requirements into production-grade credit modeling solutions.
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Ensure model robustness, accuracy, and compliance through rigorous validation, back-testing, and performance monitoring.
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Develop and maintain automated ML pipelines for data ingestion, feature engineering, model training, and deployment across large-scale credit datasets.
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Implement and enhance MLOps practices, including model integration, model monitoring.
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Research and experiment with innovative modeling techniques (e.g., gradient boosting, neural networks, graph-based learning) to improve credit decisioning capabilities.
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Mentor junior team members, conduct peer code reviews, and promote engineering excellence within the credit modeling domain.
Required Qualifications
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Bachelor s or Master s degree in Computer Science, Statistics, or a related quantitative field.
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6+ years of experience in machine learning model development and deployment, preferably in the financial services or credit risk domain.
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Strong programming proficiency in Python and SQL, with hands-on experience using PySpark for large-scale data processing.
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Deep understanding of ML frameworks such as TensorFlow, Keras, or PyTorch.
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Expertise in distributed computing, scalable data pipelines, and model optimization techniques.
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Proven experience deploying models in production cloud environments (AWS, GCP, or Azure).
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Demonstrated ability to write clean, well-documented, and production-ready code.
Preferred Qualifications
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Experience in credit risk modeling.
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Understanding of model governance frameworks, ML explainability (e.g., SHAP, LIME), and regulatory compliance.
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Familiarity with feature store architectures, model drift detection, and automated model retraining workflows.
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Knowledge of data privacy and compliance practices relevant to credit data.
Subsidiary
PayPal
Travel Percent
0
PayPal does not charge candidates any fees for courses, applications, resume reviews, interviews, background checks, or onboarding. Any such request is a red flag and likely part of a scam. To learn more about how to identify and avoid recruitment fraud please visit .
For the majority of employees, PayPals 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
We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit .
Who We Are
Commitment to Diversity and Inclusion
PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at .
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