Machine Learning Engineer Job Description
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. The successful candidate will work closely with the Data Analytics and Data Engineering teams to ensure that the models are trained on high-quality data and integrated into production systems.
The ideal candidate will have a strong understanding of machine learning techniques for predictive modeling, classification, and regression. They will be proficient in statistical and machine learning techniques and have experience working with datasets generated from cloud environments such as AWS and Snowflake.
In addition to technical responsibilities, the ML Engineer will coach and mentor fellow data analysts and engineers, ensuring efficient delivery through effective planning, prioritizing, and releasing their work. They will also exhibit and foster the company culture and operating principles.
Key Responsibilities:
* Apply advanced machine learning models to predict and model creditworthiness, transaction labeling, identity mapping, underwriting, cash flow, lease renewals, and other key financial factors.
* Work closely with the Data Analytics and Data Engineering teams to ensure that models are trained on high-quality data and integrated into production systems.
* Develop and deploy machine learning models utilizing datasets generated from cloud environments such as AWS and Snowflake.
* Translate model insights into actionable strategies that drive business decisions and financial inclusion.
* Coach and mentor fellow data analysts and engineers.
Required Skills and Qualifications:
Core Competencies:
* Superb programming, software, and data development skills.
* Strong communication skills.
* High standards.
* Balancing velocity with long-term goals.
* Heart of a teacher.
* Getting work done and driving excellence.
* Adaptability.
Knowledge & Background:
* Mastery degree in mathematics, statistics, economics, computer science, or other quantitative disciplines with a focus on data analysis.
* Relevant bachelor's degree in a STEM field with 10+ years of relevant work experience in Machine Learning and Statistics.
Above and Beyond:
* PhD degree in mathematics, statistics, economics, computer science, or other quantitative disciplines with a focus on data analysis.
* Experience working in FinTech or PropTech sectors.
* Familiarity with startup environments.
* Software engineering experience.
* Compliance knowledge.
Benefits:
* Competitive salary.
* Remote first work environment.