Join a dynamic project focused on developing a robust machine learning‑driven payments retry system to enhance ECOM transaction success rates. This full‑time contract role is fully remote, offering the opportunity to lead the design and implementation of advanced ML solutions for a critical business function. You will collaborate with cross‑functional teams to architect, build, and deploy scalable models that directly impact payment reliability and customer experience.
Responsibilities
- Design, develop, and deploy machine learning models for payment retry optimization
- Analyze transaction data to identify failure patterns and inform model improvements
- Collaborate with engineering and product teams to integrate ML solutions into production systems
- Monitor model performance, conduct A / B testing, and iterate based on results
- Ensure solutions are scalable, secure, and compliant with industry standards
- Document processes, models, and system architecture for knowledge sharing
Skills and Requirements
Proven experience in machine learning engineering, with a focus on payments or financial systemsStrong proficiency in Python and ML frameworks (TensorFlow, PyTorch, or similar)Deep understanding of data modeling, feature engineering, and algorithm selectionExperience with cloud platforms (AWS, GCP, or Azure) and deploying ML models in productionFamiliarity with payment processing systems, ECOM transaction flows, and retry logicExcellent problem‑solving skills and ability to work independently in a remote environmentStrong communication skills for cross‑functional collaborationBachelor’s or Master’s degree in Computer Science, Engineering, or related fieldAbout Twine
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Seniority level : Mid‑Senior level
Employment type : Contract
Job function : Software Development
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