Job Description

Key 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

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