The company is looking to solve credit innovation, credit risk, and fraud detection problems using advanced analytics to deliver responsible financial products.
Requirements
- Proficiency in Python (required)
- Working knowledge of SQL for data extraction and analysis
- Experience with data exploration, modeling, and business analytics
- Exposure to AWS (particularly SageMaker), Databricks, or Vertex AI is a plus but not required
- Prior experience in credit risk, fraud, or financial services is helpful but not mandatory
- Demonstrated ability to follow structured problem-solving approaches and deliver clean, documented work
Responsibilities
- Work on cross-functional projects supporting credit risk, fraud detection, and customer analytics
- Review model performance and analytical work produced by peers to ensure accuracy and consistency
- Design and conduct data analyses to inform business decisions, using Python and other tools
- Collaborate closely with stakeholders to understand business needs and translate them into analytical projects
- Present analytical results to technical and non-technical audiences
- Contribute to internal best practices and support a culture of rigorous, high-quality analytics
Other
- Degree in a quantitative field (e.g., Statistics, Mathematics, Biostatistics, Physics, Chemistry, Biology, or related discipline)
- Typically 2–4+ years of hands-on experience in data science or analytics, including exposure to financial services, fintech, or credit data (preferred)
- Strong communication skills; ability to clearly explain analytical work and its business implications
- Critical thinking and intellectual curiosity
- Business acumen; understands how analysis ties into outcomes
