Machine Learning Engineer Role Summary
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* This role involves developing and deploying 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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Key Responsibilities:
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* Collaborate with the Data Analytics and Data Engineering teams to ensure models are trained on high-quality data and integrated into production systems.
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* Create interpretable, accurate, and scalable predictive models utilizing datasets generated from our cloud environments.
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* Translate model insights into actionable strategies that drive business decisions and financial inclusion.
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* Cochain and mentor fellow data analysts and data engineers.
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* Ensure efficient delivery through effective planning, engaging with others, prioritizing, and developing, testing, and releasing work.
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* Foster company culture and operating principles.
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Technical Skills:
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* Strong programming skills in Python and SQL.
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* 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.
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* Knowledge of statistical and machine learning techniques for predictive modeling, classification, and regression.
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* Experience 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.
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* Experience implementing DataOps, MLOps, and/or DevSecOps in the AI, ML, and software development lifecycle.
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Qualifications:
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* 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.
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* Very strong experience in AI and ML in the financial technology industry, including working with credit and financial datasets.
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* Proven track record in building and deploying machine learning models, with a strong understanding of the theory and tradeoffs behind these techniques.
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* Proficiency in statistical and machine learning techniques for predictive modeling, classification, and regression.
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* Cloud expertise, especially with AWS services.
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Benefits:
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* Competitive salary.
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* Remote-first work environment with flexibility to get work done efficiently.
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About Us:
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We invest in our people with benefits designed to help you thrive both personally and professionally.