Machine Learning Engineer
Description
Job Summary
ClearGrid is seeking an innovative and hands-on ML Data Scientist to join our Collections and Portfolio Data Science this role you will own the end-to-end lifecycle of cutting-edge AI/ML models designed to optimize recovery efforts for unsecured credit products (BNPL installment loans etc.). You will act as a technical leader driving data strategy and deploying Agentic AI solutions that directly impact hundreds of thousands of customers while ensuring model fairness and regulatory compliance.
Key Responsibilities
Model Development & Lifecycle Ownership:
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Design build and deploy ML models to predict default risk and recovery probabilities for short-term lending products.
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Take complete hands-on ownership of the model lifecycle from initial research to production monitoring and automated retraining.
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Implement creative statistical approaches including causal analysis reinforcement learning and natural language processing.
Data Strategy & Engineering:
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Build efficient reusable data pipelines for feature generation and model scoring using Python and SQL.
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Architect and deploy Agentic AI infrastructures utilizing both proprietary and commercially available tools.
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Collaborate with engineering teams to integrate models into production environments seamlessly.
Domain-Specific Optimization:
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Develop models for call center performance utilizing causal analysis and multi-armed bandits to optimize outreach.
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Manage collection modeling concepts such as PD calibration reject inference and risk segmentation.
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Partner with agency and portfolio purchase teams to align model outputs with actionable business lending decisions.
Compliance & Infrastructure Evolution:
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Ensure all models meet strict standards for fairness interpretability and adverse action logic.
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Contribute to the continuous evolution of ClearGrids ML infrastructure to improve the efficiency of our AI ecosystem.
Requirements
Educational & Professional Experience:
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Advanced Degree (Ph.D. / MS) in Computer Science Data Science AI Mathematics or a related quantitative field.
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35 years of professional experience in AI Science or Machine Learning.
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Fintech Expertise: Significant experience in credit risk with a deep understanding of payment systems banking and lending products.
Technical Skills:
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Programming: Authoritative knowledge of Python and SQL.
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Frameworks: Proficiency in TensorFlow PyTorch and tree-based models.
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ML Techniques: Expertise in deep learning clustering time series and reinforcement learning.
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Data Engineering: Proven ability to build scalable pipelines and frameworks for large complex datasets.
Soft Skills:
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Strong problem-solving abilities and the communication skills necessary to defend model logic to stakeholders.
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A results-oriented innovator mindset capable of thriving in a fast-paced collaborative environment.
Preferred Qualifications
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Cloud Infrastructure: Experience with GCP (Vertex AI) or AWS (SageMaker) and orchestration tools like Apache Airflow.
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MLOps: Strong background in automated retraining version control and model monitoring pipelines.
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Experimentation: Expertise in A/B testing design and advanced statistical analysis.
Employment Type : Full Time
Experience: years
Vacancy: 1