Posted 17 days ago
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Lead the design, development, and production deployment of machine learning models with end-to-end ownership, including optimization for memory and latency. Perform deep statistical analysis, feature engineering with SQL, and build containerized models with CI/CD and monitoring to track model performance and drift. Collaborate on API design and deploy models in production, with emphasis on fraud detection or credit underwriting use cases and strong stakeholder communication. Required skills include high proficiency in Python, containerization (Docker), and a solid foundation in ML/DL and statistics.
- Compensation
- Not specified
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Currency: Not specified
Full Job Description
What you will do
• Design, develop, and ship production-grade machine learning models with full ownership, considering everything from memory footprint to latency.
• Dive deep into statistical analysis, probability, and machine learning/deep learning models. • • Critically evaluate existing solutions and develop novel approaches where needed. A foundational understanding of NLP architectures like Transformers is a plus.
• Build and maintain containerized models and develop model monitoring solutions to track metrics like variable drift.
• Create and manage CI/CD pipelines for machine learning models and contribute to the design and development of APIs.
• Utilize SQL proficiency to perform in-depth data analysis and feature engineering.
Who you are
• Proven software engineering skills with experience designing, developing, and deploying ML models in production. Experience with deploying models on Scoring Platform is highly desirable.
• High proficiency in Python.
• Strong quantitative foundation with deep understanding of statistical analysis, probability, and a wide range of ML and DL models.
• Hands-on experience with containerization (Docker), CI/CD pipelines, and model monitoring.
• Experience in API schema design and development, and building containerized applications (e.g., using Docker).
• Excellent communication and stakeholder management skills.
• Experience working with consumer or partner Fraud Detection/Credit Underwriting would be a plus.
Awesome to have
• An academic background in Physics, ML, Data Science, Mathematics, or Biology.
• Prior experience as a Senior Data Scientist, ideally within a regulated environment or fintech context.
Please include a CV in English.
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