Machine Learning Engineer, Credit Modeling

View full description

Requirements:

• 3+ years of professional experience in developing and implementing credit ML models or systems within the banking or FinTech industry.
• Educational background in Computer Science, Engineering, Mathematics, or related field.
• Good understanding of supervised and unsupervised learning, deep learning, reinforcement learning, and ensemble methods.
• Proficiency in Python, PostgreSQL, Java/Scala.
• Strong knowledge of database management systems (MySQL, PostgreSQL), data wrangling, feature engineering, ETL processes, and SQL databases.
• Familiarity with Apache Spark.
• Experience with Docker, Kubernetes, and cloud platforms (AWS preferred). Knowledge of MLOps practices.
• Expertise in TensorFlow, PyTorch, Keras, scikit-learn, and XGBoost.
• Proficiency with Jupyter Notebooks, Git, Jenkins, Apache Spark, and Hadoop.

Responsibilities:

• Design and implement credit ML models and systems, ensuring robust and scalable solutions.
• Develop end-to-end ML pipelines for credit modeling, including data collection, preprocessing, model training, and deployment.
• Collaborate with data scientists and software engineers to integrate ML models into production environments.
• Utilize cloud platforms (AWS preferred) to scale ML solutions, manage resources, and optimize costs.