Job description

The Product Scientist is responsible for developing and documenting credit scoring models and other complex algorithms which are the foundation of the products used by customers to improve their credit scores.

The Product Scientist will be equal parts Data Scientist and Quantitative Researcher the ideal candidate must have the research skills to understand how traditional credit scoring models work as well as how new data can be applied to quantify the drivers of credit scores. With quantified drivers of credit scores, downstream gains such as optimal scenarios can be constructed.

Essential Functions:
As the Product Scientist, you will

• Develop novel, new methods of credit scoring and other complex algorithms as well as documenting and explaining that process
• Interaction with Executive Leadership
• Work with engineers to ensure the model is properly translated to production
• Run statistical analysis
• Run tests and experiments to ensure quality
• Mentor team members

Competencies and Criteria for Success

Job Specific Competencies:

• Technical / Analytical
• Articulate Communicator
• Product Mindset
• Complex Problem Solver
• Sense of Urgency
• Team oriented
• Adaptable
• Detail orientation

We look for top performers who:

• Act - Value actions and results, not just ideas
• Perform Embrace the team, we succeed or fail together
• Pivot Comfortable to change course in support of company objectives
• Engage Be part of the team, be nice, get involved
• Adapt React positively to new information
• Influence Positively impact what we do and how we do it
• Learn Passionate about continuous improvement and learning

Required Education and Experience

• MS\Ph.D. in Statistics, Economics, Operations Research, Applied Mathematics or similar
• 5+years in statistical analysis on observational data
• Experience with Python, a must

Additional, Ideal, Education and Experience

• Experience with R, SAS, Stata, Matlab. JMP
• Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)
• Familiarity with Mathematical Optimization
• Familiarity with Git and CICD
• Experience with Data Visualization toolkit (Tableau, PowerBI, Looker)
• Dataiku experience, a major plus
• Experience in a start-up environment, a plus

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