Credit Risk Data Scientist - Platform & ML Modeling

Indodana; Jakarta Pusat; On-site; IDR 89,280,000 - 167,400,000; Full time

Job summary

Indodana is seeking fresh graduates with experience in manipulating datasets and building statistical models for credit risk using machine learning. You will partner with business, product, and engineering teams to explore, analyze, and solve challenging lending problems, while improving our data framework in a fast-paced environment.

You will perform deep-dive explorations, build models, and create dashboards to monitor performance, with opportunities to work with our robust data infrastructure

Qualifications

• Bachelor degree in an analytical or quantitative discipline (e.g. math, statistics, engineering, computer science).
• Experience with statistical languages such as R, Python, SAS, SQL or advanced MS Excel is a plus.
• Good communication skills and ability to work in a team.
• Excellent problem-solving skills and willingness to learn new technologies.
• Willingness to learn independently and take ownership of projects.
• Not afraid to explore data and build statistical models.

Responsibilities

• Perform features selection, parameter binning, and optimize custom predictive ML models for credit risk scoring.
• Query, process, cleanse, and verify the integrity of data used for analysis.
• Analyze key metrics to determine risk and identify improvements.
• Create reports and dashboards to monitor model impact and performance.
• Help build data ingredients needed for modelling and maintain the risk model platform.
• Provide advice on efficiency gains and new credit risk modelling methodologies.

Skills

Data analysis

Statistical modeling

Problem solving

Team collaboration

Communication skills

Education

Bachelor degree in analytical or quantitative discipline

Tools

R

Python

SAS

SQL

MS Excel

Job description

Indodana is seeking fresh graduates with experience in manipulating datasets and building statistical models for credit risk using machine learning. You will partner with business, product, and engineering teams to explore, analyze, and solve challenging lending problems, while improving our data framework in a fast-paced environment.

You will perform deep-dive explorations, build models, and create dashboards to monitor performance, with opportunities to work with our robust data infrastructure