Senior Business Analyst, Credit & Analytics
New
J
JeevesCredit risk
Listing location: Argentina; Structured job location: Argentina, Able to work with meaningful overlap with Latin American business hoursFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- Professional fluency in English; Fluency in Spanish and/or Portuguese (preferred)
- Experience
- 3–7 years of analytics experience in credit risk
- Required Skills
- PythonSQL
Requirements
- 3–7 years of analytics experience in credit risk, with hands-on work on commercial or SMB credit in cards, payments, lending or a related industry.
- Advanced SQL skills, including writing queries against large, messy datasets and validating data quality.
- Working proficiency in Python for analysis and statistical modeling, including regression, segmentation and clustering.
- Direct experience with external or alternative data sources such as bureau, banking, open finance or tax data; integrating or cleaning these sources is preferred.
- Experience using AI tools such as Claude, ChatGPT or Gemini in analytical work.
- A track record of turning analysis into an implemented credit policy or strategy change with measurable results.
- Ability to work independently and take ownership.
- Clear written and verbal communication, including explaining model results or data issues to non-technical stakeholders.
- Professional fluency in English.
- Ability to work with meaningful overlap with Latin American business hours.
- Experience with GitHub or other version control is a plus.
- Knowledge of Latin American credit data and open finance ecosystems, experience with risk or scoring models, collections strategy or early-warning programs, and visualization tools such as Tableau or Metabase are preferred.
Responsibilities
- Lead integration and validation of external credit bureau, banking, open finance, tax and financial data, partnering with engineering on pipelines and data quality.
- Own cleanup of customer data consents and connections so external data can be reliably pulled and refreshed in line with local requirements.
- Replace manual credit and portfolio processes with repeatable, documented SQL/Python workflows.
- Define data quality checks and documentation for the team.
- Develop and refine underwriting criteria, credit limit strategies, and customer management strategies using internal performance and external data.
- Identify high-risk customers early and build processes to mitigate losses.
- Define portfolio KPIs, build dashboards, and establish early-warning signals and monitoring routines.
- Provide Collections with segmentation and prioritization insights, and contribute to loss forecasting and risk-adjusted return analysis with Finance.
- Develop, validate and monitor credit risk models, and help define rules and data requirements for automated credit decisioning.
- Translate model results into recommendations for credit leadership and business partners.
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