AddressKey Responsibilities:
- Develop machine learning models that drive actionable insights to support business decisions.
- Working with large and complex datasets from various internal sources to generate insights.
- Develop frameworks for pre-approval strategies for new and within-funnel users. Monitor funnel efficiencies and take actions to further improve them.
- Explore and evaluate potential alternate data sources for incremental value in pre-approval programs.
- Develop and implement propensity models to predict customer behavior and preferences.
Qualifications:
- Bachelor's or Master's degree in a quantitative field (e.g., Computer Science, Statistics, or related field)
- 3+ years of hands-on experience in data science and analytics roles.
- Strong proficiency in programming languages such as Python or R.
- Demonstrated experience with machine learning algorithms and statistical modeling techniques.
- Excellent problem-solving skills and the ability to think analytically.
- Effective communication skills and the ability to work collaboratively in a team environment.
- Good business acumen with a strong ability to solve business problems through data-driven quantitative methodologies
Preferred Skills:
- Experience with big data technologies (e.g., Spark).
- Industry-specific domain knowledge, particularly in lending or financial services.
- Experience with unstructured data handling
- Understanding of credit bureaus and non-traditional data providers will be a plus
