We are seeking a skilled Machine Learning Engineer to work with our Data Analytics and Data Engineering teams.
The successful candidate will be responsible for applying advanced machine learning models to predict and model creditworthiness, transaction labeling, identity mapping, underwriting, cash flow, lease renewals, and other key financial factors.
Key Responsibilities:
* Create interpretable, accurate, and scalable predictive models utilizing datasets generated from AWS and Snowflake environments.
* Translate model insights into actionable strategies that drive business decisions and financial inclusion.
Requirements:
* Master's degree in mathematics, statistics, economics, computer science, or other quantitative disciplines with a focus on data analysis.
* Strong experience in AI and ML in the financial technology or service industry, including working with credit and financial datasets.
* Proven track record in building and deploying machine learning models, with a strong understanding of the theory and tradeoffs behind these techniques.
* Proficiency in statistical and machine learning techniques for predictive modeling, classification, and regression.
* Very strong knowledge of Python and SQL.
* Strong experience with AWS cloud services and tools, including AWS SageMaker for model development, training, and deployment.
* Experience working with model registry tools such as MLflow, SageMaker Model Registry, or other similar systems.
* Experience implementing DataOps, MLOps, and/or DevSecOps in the AI, ML, and software development lifecycle.
* Experience building ML models with PyTorch, Scikit-learn, and GenAI models.
Benefits:
* Competitive salary
* Remote first work environment
About this role:
This is an exciting opportunity for a talented Machine Learning Engineer to join our team and contribute to our mission of driving business decisions and financial inclusion through data-driven insights.