Job description

About Us

Ringkas is helping to democratize home ownership in Indonesia, which facilitates access to financing to help home seekers become homeowners. Ringkas is built by experienced founders from Google, Amazon, and Dell, with backgrounds in tech who have scaled products and digital businesses worldwide. We are backed by VCs and several prominent angel investors who have built FinTech platforms for millions of people in Indonesia and the US.

Our vision is to democratize home ownership and make it accessible for everyone. Our mission is to make homeownership simpler, faster, and accessible for all. We believe homeownership should be fast, transparent, and low-cost for all. Home and mortgage finance has operated through traditional opaque systems for years. We are redefining the process by building an end-to-end digital infrastructure, leveraging technology to enhance efficiency and deliver a seamless customer experience.

At Ringkas, we leverage various models throughout our processes to ensure effective risk assessment and decision-making. Our data scientists in Underwriting Innovation & Analytics team explore innovative data sources and methodologies to build predictive models that address challenges in origination and underwriting

RESPONSIBILITIES:

• Develop and refine models for digital origination and underwriting, which consists of credit scoring, behavioral scoring, risk segmentation, property valuation (AVM), income, and capacity prediction
• Develop calculation engines and customer lifetime value models for various financial products. Later on, this will include loss curve, take-up curve, and prepayment models.

REQUIREMENT:

• Minimum 3 years of experience in developing models for origination and underwriting.
• A Bachelor or Master in Econometrics, Statistics, Math, or Actuary. [or] Bachelor with a strong quantitative component such as Engineering with additional training in data science methodologies and risk modeling.
• Good proficiency in regression (logistic), machine learning (random forest, GBM, and neural networks), AI decision models (combining machine learning techniques with rule-based approaches), Markov chains, time series, SVM, CART, and optimization models.
• Excellent verbal and written communication skills in English and Indonesian.
• Proven ability to prioritize tasks and manage multiple projects effectively.
• Good proficiency in automated data processing with Python (or other programming languages).

Nice to Have:

• Experience with decisioning platforms such as FICO, SAS, or CRIF.