Job Title: Lead Data Modeler
About the Role
We are seeking a highly skilled ML Engineer to develop and deploy advanced machine learning models that predict and model creditworthiness, transaction labeling, identity mapping, underwriting, cash flow, lease renewals, and other key financial factors.
Key Responsibilities
* Collaborate with Data Analytics and Data Engineering teams to ensure high-quality data is used for model training and integration into production systems.
* Create interpretable, accurate, and scalable predictive models using datasets generated from AWS and Snowflake environments.
* Translate model insights into actionable strategies driving business decisions and financial inclusion.
* Coach and mentor fellow data analysts and engineers to improve efficiency and quality of work.
Requirements
* Master's degree in mathematics, statistics, economics, computer science, or other quantitative disciplines with a focus on data analysis.
* Very 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 theory and tradeoffs behind these techniques.
* Proficiency in statistical and machine learning techniques for predictive modeling, classification, and regression.
* Strong knowledge of Python and SQL programming languages.
* Experience with cloud services such as AWS SageMaker, AWS Bedrock, and Snowflake for data warehousing and efficient handling of large-scale data storage and processing.
* Familiarity with model registry tools such as MLflow, SageMaker Model Registry, or other similar systems to track, version, and manage machine learning models throughout their lifecycle.
* Experience implementing DataOps, MLOps, and/or DevSecOps in the AI, ML, and software development lifecycle.
Benefits
* Competitive salary.
* Remote first work environment.