Senior Machine Learning Engineer
We are seeking a highly skilled 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.
This role requires strong collaboration with key managers, product owners, and other peers and cross-functional partners that rely, produce, and interact with the data domain across the organization. The successful candidate will focus on creating interpretable, accurate, and scalable predictive models utilizing datasets generated from our cloud environments. Additionally, you will translate model insights into actionable strategies that drive business decisions and financial inclusion.
Key Responsibilities:
* Design and implement advanced machine learning models to solve complex problems in the financial technology industry
* Collaborate with cross-functional teams to integrate models into production systems and ensure high-quality data
* Translate model insights into actionable strategies that drive business decisions and financial inclusion
* Cochampion and mentor fellow data analysts and engineers to improve team performance
* Ensure efficient delivery through effective planning, prioritization, and project management
Requirements:
* Master's degree in mathematics, statistics, economics, computer science, or other quantitative disciplines with a focus on data analysis. A relevant bachelor's degree with 10+ years of relevant work experience in Machine Learning and Statistics is also considered.
* 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
Benefits:
* Competitive salary
* Remote first work environment
Above and Beyond:
* Specialized knowledge and background in PhD-level mathematics, statistics, economics, computer science, or other quantitative disciplines with a focus on data analysis
* FinTech/PropTech expertise
* Startup experience
* Software engineering experience with microservices
* Compliance knowledge in SOC2-certified, ISO-certified, or similar organizations
About Us:
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