Machine Learning Engineer Opportunity
We are seeking a highly skilled Machine Learning Engineer to join our team. As a key member of our organization, you will be responsible for designing and implementing 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. The ideal candidate will have a strong understanding of machine learning techniques and experience working with large datasets. Additionally, you will translate model insights into actionable strategies that drive business decisions and financial inclusion.
The successful candidate will also be responsible for coaching and mentoring fellow data analysts and engineers. You will ensure efficient delivery through effective planning, engaging with others, prioritizing, and developing, testing, and releasing your work. We foster a culture of collaboration and innovation, and we are looking for someone who shares these values.
Key Responsibilities:
* Design and implement advanced machine learning models using Python and SQL.
* Work closely with the Data Analytics and Data Engineering teams to ensure high-quality data integration.
* Translate model insights into actionable strategies that drive business decisions and financial inclusion.
* Coach and mentor fellow data analysts and engineers.
Requirements:
* Masters degree in mathematics, statistics, economics, computer science, or other quantitative disciplines with a focus on data analysis.
* Very strong experience in AI and ML in the financial technology or service industry.
* Strong knowledge of Python and SQL programming languages.
* Experience working with cloud-based data warehousing platforms like Snowflake.
* Excellent communication and problem-solving skills.
What We Offer:
* A competitive salary and benefits package.
* A remote first work environment that trusts you to get your work done.
* Opportunities for growth and professional development.