Machine Learning Engineer Role Overview
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We are seeking a highly skilled Machine Learning Engineer to join our team. The ideal candidate will have a strong background in machine learning, statistics, and programming.
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About the Opportunity
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This role involves applying advanced machine learning models to predict and model creditworthiness, transaction labeling, identity mapping, underwriting, cash flow, lease renewals, and other key financial factors.
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The successful candidate 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.
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Key Responsibilities
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* Design and implement advanced machine learning models using datasets generated from AWS and Snowflake environments.
* Translate model insights into actionable strategies that drive business decisions and financial inclusion.
* Coach and mentor fellow data analysts and data engineers.
* Ensure efficient delivery through effective planning, engaging with others, prioritizing, and developing, testing, and releasing your work.
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Requirements
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The ideal candidate will possess:
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* 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 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, and AWS Bedrock for building and fine-tuning foundation models.
* Experience in working 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.
* Experience building ML models with PyTorch, Scikit-learn, and GenAI models.
* Familiarity with Snowflake for cloud data warehousing, data integration, and efficient handling of large-scale data storage and processing.
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Benefits
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We offer a competitive salary and remote-first work environment, where we trust you to get your work done.
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