Sign up with

Already have an account? Log in here

Need some help?
Talk to us at +91 7670800001

Data Scientist - Risk Platform at Cermati.com

Special capital Region of Jakarta, Java, Indonesia -

Full Time

Start Date

Immediate

Expiry Date

03 Feb, 26

Salary

0.0

Posted On

05 Nov, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Manipulation, Statistical Models, Machine Learning, Credit Risk, Data Analysis, Feature Selection, Predictive Modeling, Data Cleansing, SQL, R, Python, SAS, Communication Skills, Problem-Solving, Project Ownership, Team Collaboration

Industry

Financial Services

Description

Job Description We’re looking for fresh graduates with experience in manipulating datasets and building statistical models for credit risk by leveraging machine learning techniques. You will partner with business, product, and engineering team to explore, determine, analyze, propose, and solve some of the most challenging business problems in lending and reduce risk. You will perform deep-dive exploration and analysis to find improvements in our existing framework. You will be submerged in a fast-paced environment working tightly in a strong team of data scientists and experience firsthand our robust data infrastructure. Responsibilities Perform features selection, parameter binning, and optimize custom predictive machine learning models for credit risk scoring Query, process, cleanse, and verify the integrity of data used for analysis Analyze key metrics to determine risk and explore areas for improvements Create reports and dashboards to monitor model impact and performance Help build the variety of data ingredients needed to do modelling effectively Maintain the credit risk model platform which is utilized by the team Provide advice and guidance on potential efficiency gains and new state-of-the-art credit risk modelling methodologies Qualifications Bachelor degree in an analytical or quantitative discipline (e.g. math, statistics, engineering, computer science), however other disciplines will be considered Experienced in using statistical computer languages such as R, Python SAS, SQL, or advanced MS Excel skills is a plus. Have good communication skills and able to work together in a team Excellent problem-solving skills and have the drive to learn and master new technologies and techniques Willingness to learn new skills independently and have a strong sense of project ownership Not afraid to get your hands dirty to explore data and build statistical models

Responsibilities

You will perform features selection, parameter binning, and optimize custom predictive machine learning models for credit risk scoring. Additionally, you will analyze key metrics to determine risk and explore areas for improvements.