Machine Learning Engineer Opportunity
We are seeking a talented Machine Learning 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.
This role will work closely with the Data Analytics and Data Engineering teams to ensure the models are trained on high-quality data and integrated into production systems. Collaboration is key in this role, as you will be working with cross-functional partners including Data Engineers, Data Analysts, Backend Engineers, Marketing, and Sales teams.
Key Responsibilities:
* Develop and train machine learning models using datasets from AWS and Snowflake environments.
* Translate model insights into actionable strategies that drive business decisions and financial inclusion.
* Cross-functionally collaborate with Data Engineers, Data Analysts, Backend Engineers, Marketing, and Sales teams.
* Mentor and coach fellow data analysts and engineers.
Requirements:
* Master's degree in mathematics, statistics, economics, computer science, or other quantitative disciplines with a focus on data analysis. Relevant bachelor's degree with 10+ years of relevant work experience also considered.
* 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.
* Knowledge of Python and SQL programming languages.
* Strong experience with AWS cloud services and tools, including AWS SageMaker for model development, training, and deployment, and AWS Bedrock for building and fine-tuning foundation models.
* Experience implementing DataOps, MLOps, and/or DevSecOps in the AI, ML, and software development lifecycle.
* Familiarity with Snowflake for cloud data warehousing, data integration, and efficient handling of large-scale data storage and processing.
Competitive Benefits:
* Competitive salary.
* Remote first work environment with trust and flexibility.