Lead Data Scientist - Collections (911605)

Greenville, SC, US, 29601

Purpose Financial

Purpose Financial, Inc. is here to serve you with innovative consumer financial services that includes a diverse suite of credit products.

View all jobs at Purpose Financial

Apply now Apply later

COMPANY:

Purpose Financial, Inc.

TITLE:

Lead Data Scientist – Collections

DUTIES:

Develop and implement advanced statistical and machine learning techniques to predict customer delinquency and default, to help identify high-risk accounts. Utilize statistical techniques to analyze historical collections data and derive actionable insights that inform strategy enhancements. Discover insights from additional data sources to understand/influence consumer financial behavior and continue to enhance machine learning models as additional data becomes available. Collaborate with collections operations team to build and improve monitoring of portfolio KPIs and collections strategy. Develop automated processes and procedures to streamline data analysis and reporting. Monitor trends in relevant KPIs and report on key insights on a regular basis. Stay up-to-date with the latest trends in data science and collections and apply these insights to improve our practices. Independently design experiments to enable longer term optimization of decisions as relating to collections. Assist junior modelers with model design, construction, implementation, monitoring, and delivering model results to leadership. Hybrid work from home permitted two (2) days a week.

SCHEDULE:

40 hours per week, Monday through Friday

LOCATION:

Purpose Financial, Inc., 322 Rhett Street, Greenville, SC 29601

REQUIREMENTS:

Bachelor’s degree in Applied Statistics, Data Science, Computer Science, Economics, Engineering, Mathematics, Statistics or related quantitative field and three (3) years of experience as a Data Analyst, Data Scientist, Risk Management, Consumer Lending or related role where required experience was gained.

SPECIAL SKILLS:

Also requires two (2) years of experience in the following:

  • Build machine learning models using R or Python.
  • Exposure to reporting tools such as Tableau, PowerBI.
  • Experience with the different types of machine learning techniques, Python data science stack such as Pandas, scikit-learn, NumPy, XGBoost, SHAP, notebook environments, etc.
  • SQL.
  • Ability to combine data from multiple sources to analyze and interpret business performance.
  • Ability to understand and ensure compliance with policies, procedures, and laws governing our industry/business and product

CONTACT:

To apply, send resume to: Lalia Taylor at ltaylor@teampurpose.com. Please reference job title and location.

Apply now Apply later

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Job stats:  0  0  0

Tags: Computer Science Data analysis Economics Engineering KPIs Machine Learning Mathematics ML models Model design NumPy Pandas Power BI Python R Scikit-learn SQL Statistics Tableau XGBoost

Regions: Remote/Anywhere North America
Country: United States

More jobs like this