Data Scientist

The Role

Reporting directly to the Director of Data Science, you will play a crucial role in driving customer adoption by producing models that demonstrate the impact of our cashflow scores and attributes on customers’ bottom lines. Your analytical skills, coupled with experience in building highly-performing statistical models and knowledge of credit risk in the US, will be instrumental in improving our data products and in influencing our product roadmap.

Responsibilities

This role involves engaging with customers during the presales phase to demonstrate the value and effectiveness of our scores and attributes through building custom models. Therefore, the ideal candidate will:

• Analyze the impact of Pave’s scores and attributes on customer performance metrics, particularly focusing on increasing approvals and reducing defaults, and present these insights directly to clients.

• Design, implement, and evaluate experiments to test the effectiveness of new attributes and models.

• Stay up-to-date with industry best practices and advancements in data science, AI and ML, and credit risk analytics tools, and technologies.

• Help ensure all models, attributes, and analyses are compliant with fair lending practices, translating these considerations into the attributes and analyses we conduct for credit risk.

Requirements

• Strong analytical and data exploratory skills with the ability to ask the right questions, interpret data and provide actionable insights.

• Ability to clearly communicate findings and insights to both technical and non-technical stakeholders, including external partners and customers.

• Demonstrated experience of going from data analysis to building highly performing ML models, including feature engineering and measuring performance.

• Solid understanding of machine learning libraries like scikit-learn, and tree ensemble packages like XGBoost.

• Strong problem-solving skills and a detail-oriented mindset.

• Work experience in US fintech or in the financial industry.