Role overview
As Senior Data Scientist, you’ll take on a high-impact role focused on building and scaling advanced models that balance customer acquisition with strong risk management. You’ll lead initiatives to allow more customers while carefully managing risks, working with advanced analytics and machine learning techniques to distinguish between high-risk and trustworthy profiles.
What you'll work on
- Design, build, and evaluate machine learning and deep learning models for classification, regression, recommendation, NLP, computer vision, and time-series forecasting.
- Apply deep learning techniques (e.g., CNNs, RNNs, LSTMs, Transformers) to solve complex, data-intensive problems.
- Lead the development of ML products, from model prototyping through production deployment, performance monitoring, and continuous improvement.
- Select appropriate architectures, optimize model performance, and use proper evaluation metrics based on the use case.
- Collaborate with product managers and engineers to translate business challenges into deployable solutions using AI/ML.
- Design automated pipelines for data preprocessing, feature engineering, training, and inference (batch or real-time).
- Evaluate model drift, monitor performance post-deployment, and implement retraining pipelines as part of a production MLOps system.
- Mentor junior data scientists, contribute to code reviews, and lead technical discussions across the data science and engineering teams.
Tags & focus areas
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