About the Role
We are seeking a highly skilled Machine Learning Engineer to join our team. The successful candidate will have expertise in applying advanced machine learning models to predict and model creditworthiness, transaction labeling, identity mapping, underwriting, cash flow, lease renewals, and other key financial factors.
This role requires close collaboration with the Data Analytics and Data Engineering teams to ensure high-quality data is used to train models that are integrated into production systems. You will work closely with key managers, product owners, and peers to deliver interpretable, accurate, and scalable predictive models.
You will be responsible for creating actionable strategies from model insights that drive business decisions and financial inclusion. Additionally, you will coach and mentor fellow data analysts and engineers to ensure efficient delivery through effective planning and prioritization.
Key Responsibilities
* Develop and deploy machine learning models using AWS cloud services and tools, including SageMaker for model development, training, and deployment, and Snowflake for cloud data warehousing and integration.
* Work closely with cross-functional partners to integrate models into production systems.
* Create actionable strategies from model insights to drive business decisions and financial inclusion.
* Cultivate and maintain relationships with key stakeholders to ensure alignment and communication of project goals and progress.
* Mentor and coach fellow data analysts and engineers to ensure efficient delivery through effective planning and prioritization.
Requirements and Qualifications
* A Master's degree in mathematics, statistics, economics, computer science, or other quantitative disciplines with a focus on data analysis, or a relevant bachelor's degree with 10+ years of relevant work experience in Machine Learning and Statistics.
* Very strong experience in AI and ML in the financial technology or service industry, including working with credit and financial datasets.
* A 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.
* Strong knowledge of Python and SQL programming languages.
* Experience with AWS cloud services and tools, including SageMaker and Snowflake.
* Experience implementing DataOps, MLOps, and/or DevSecOps in the AI, ML, and software development lifecycle.
Benefits
* Competitive salary.
* Remote first work environment.
About Us
We invest in our people with benefits designed to help you thrive both personally and professionally.
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