About the Role
We are seeking a skilled Machine Learning Engineer to join our team.
This is an exciting opportunity to work on 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 collaborate closely with Data Analytics and Data Engineering teams to ensure high-quality data for training and integrating models into production systems.
* You will focus on creating interpretable, accurate, and scalable predictive models using datasets from AWS and Snowflake environments.
* You will translate model insights into actionable strategies driving business decisions and financial inclusion.
* You will coach and mentor fellow data analysts and engineers, ensuring efficient delivery through effective planning and prioritization.
Core Competencies
* Superb programming skills, with ability to devise and implement solutions independently.
* Strong communication skills, with ability to translate between technical and non-technical audiences.
* High standards of quality, with continuous improvement and excellence in work.
* Balancing velocity with long-term goals, thinking big while delivering the right thing.
* Capable mentorship and inspiring others on the team.
* Prioritizing delivering high-quality outcomes and projects.
* Thriving in a dynamic environment with new challenges.
Required Skills and Qualifications
* Master's degree in mathematics, statistics, economics, computer science, or related field.
* Relevant experience in AI and ML, particularly with credit and financial datasets.
* Proven track record in building and deploying machine learning models.
* Proficiency in statistical and machine learning techniques for predictive modeling.
* Strong knowledge of Python and SQL.
* Experience with AWS cloud services and tools.
* Working with model registry tools like MLflow or SageMaker Model Registry.
* Implementing DataOps, MLOps, and/or DevSecOps in the AI and software development lifecycle.
* Building ML models with PyTorch, Scikit-learn, and GenAI models.
Benefits
* Competitive salary for a Series B startup.
* Remote first work environment, trusting you to get your work done efficiently.
Additional Information
* Familiarity with FinTech/PropTech sectors and startup environments.
* Experience working with microservices and compliance knowledge in SOC2-certified organizations.