Department Overview
Data Science uses advanced analytics and machine learning to drive data-driven decision-making. They analyze large datasets to identify trends, improve credit scoring models, and optimize lending strategies. The team develops predictive models, enhances risk assessment processes, and creates automation tools to streamline operations, ultimately improving loan performance and business outcomes.
What requirements and technical training is needed to get into this position?
Masters Degree in a related field
Experience with analytical
Experience with modeling tools
Proficiency in a coding language (we use python and SQL heavily)
What do you do on a day-to-day basis?
Develop, improve, and upkeep predictive models, engage stakeholders and collaborators
What days/hours does your team work?
Monday through Friday
8 Hours Per Day
Who are the key stakeholders and who is impacted by your work (who’s your client)?
Sales via lead prioritization
Compliance
BI/Data Analysis
Marketing
What are the metrics/KPIs used to define success?
We demonstrate efficacy of scoring models using ROC-AUC, which indicates how accurately targets are ranked. This serves as a proxy for actual uplift (improved sales metrics, e.g.).
Define the micro-culture of the department and what makes it special/unique?
Lending only has one person assigned to Data Science (DS) that works within the broader Achieve DS Guild for growth and cooperation with the larger ADR DS team.
How is the work structure – independent work or more collaboration?
Largely independent work that frequently depends on information, data, and requirements gathering
What does the future in terms of growth opportunity look like for this department?
This department is a newly formed segment; time will tell.
What systems are used in the core roles?
Google BigQuery
Jupyter Notebooks
FUSE