**The Opportunity**
We are seeking a skilled Machine Learning Engineer to develop and deploy advanced predictive models that analyze creditworthiness, transaction labeling, identity mapping, underwriting, cash flow, lease renewals, and other key financial factors. This role will collaborate closely with the Data Analytics and Data Engineering teams to ensure high-quality data and integration into production systems. Strong communication skills are essential to translate technical concepts into actionable strategies for business decisions and financial inclusion.
The ideal candidate will possess strong programming skills, with experience in software development, data analysis, and model interpretation. Proficiency in statistical and machine learning techniques, including classification and regression, is also required. Additionally, expertise in working with large datasets, cloud-based services (AWS), and model registry tools (MLflow, SageMaker Model Registry) is necessary. Experience in implementing DataOps, MLOps, and DevSecOps in the AI, ML, and software development lifecycle is also desirable.
**Key Responsibilities**
* Develop and deploy machine learning models using AWS cloud services and tools
* Collaborate with Data Analytics and Data Engineering teams to ensure high-quality data and integration into production systems
* Translate technical concepts into actionable strategies for business decisions and financial inclusion
* Implement DataOps, MLOps, and DevSecOps in the AI, ML, and software development lifecycle
**Requirements**
* Master's degree in mathematics, statistics, economics, computer science, or other quantitative disciplines with a focus on data analysis
* 10+ years of relevant work experience in Machine Learning and Statistics
* Strong experience in AI and ML in the financial technology or service industry
* Proven track record in building and deploying machine learning models
* Proficiency in statistical and machine learning techniques, including classification and regression
* Expertise in working with large datasets, cloud-based services (AWS), and model registry tools (MLflow, SageMaker Model Registry)
* Experience in implementing DataOps, MLOps, and DevSecOps in the AI, ML, and software development lifecycle
**Benefits**
* Competitive salary
* Remote first work environment