Senior Collections Analytics Specialist

Gm Financial; Xico; Hybrid; MXN 600,000 - 1,000,000; Full time

Benefits offered by this job

401K matching

Tuition assistance

GM employee auto discount

Nine company holidays

Job summary

GM Financial is seeking a Collections Analytics Senior Representative in Monterrey to drive credit recovery through advanced analytics, statistical modeling, and machine learning. You will work with Collections Operations, Credit Strategy, and BI teams to transform data into actionable insights and improve portfolio performance.

Responsibilities include building datasets, KPIs, segmentation and predictive models, running experiments, and presenting findings to guide decisions.

Qualifications

• Requires experience with data warehouses and extracting/manipulating data.
• Proficient in quantitative analysis, modeling, and ML.
• Proficient in testing/validating models and monitoring performance.
• Strong data visualization and communication skills.
• Background in MIS/Credit Strategy or BI in financial services is preferred.

Responsibilities

• Develop datasets for Collections operations and maintain data structures.
• Create KPIs, reports, and controls to support credit recovery.
• Develop segmentation, predictive, and optimization models.
• Measure model impact and monitor strategies deployed.
• Design experiments (A/B tests, RCT) and present analyses to guide decisions.
• Lead analytics projects within Collections and collaborate with Operations, Strategy, and BI teams.

Skills

Python

SQL

Statistical modeling

Machine learning

Data visualization

Excel

English

Education

Degree in Statistics/Mathematics/Engineering/Computer Science

Tools

PowerBI

SAS

R

Job description

GM Financial is seeking a Collections Analytics Senior Representative in Monterrey to drive credit recovery through advanced analytics, statistical modeling, and machine learning. You will work with Collections Operations, Credit Strategy, and BI teams to transform data into actionable insights and improve portfolio performance.

Responsibilities include building datasets, KPIs, segmentation and predictive models, running experiments, and presenting findings to guide decisions.