Data Scientist

I am looking to hire a Credit Risk Data Scientist for our client Credit Karma . At your earliest convenience, please check the job specs out and let me know if this is something you'd like to have an exploratory conversation about:

Job Title: Credit Risk Data Scientist

Rate: $58 per hour on C2C

Location: CA (remote)

Contract Duration: 6 months

Description :

Design, build, evaluate and defend machine learning models to predict credit risk for various short-term lending products (e.g., tax refund advances, BNPL, installment loans)

Collaborate with product and risk teams to ensure models align with business goals and product offering to drive actionable lending decisions

Build efficient and reusable data pipelines for feature generation, model development, scoring, and reporting using Python, SQL and CK Machine Learning and AI infrastructure

Deploy models in a production environment in collaboration with other data scientists and engineering

Collaborate with business partners to create policies utilizing model results

Implement metrics like AUC, KS, Gini to monitor, measure model performance and PSI, CSI to measure stability indices

Ensure model fairness, interpretability, and compliance with FCRA, ECOA, and other relevant regulatory frameworks

Requirements

• Degree in Mathematics, Statistics, Computer Science, or related field

• 2+ years of industrial experience in Data Science, Machine Learning and related areas

• 2+ years of industrial experience working with Python and SQL; Strong proficiency in Python, with expertise in libraries such as scikit-learn, XGBoost, LightGBM, pandas, and numpy; Solid SQL skills for data extraction and transformation across large datasets

• Experience and deep understanding of a variety of machine learning techniques, including tree-based models, regression models, time series, causal analysis, and clustering

• Ability to quickly develop a deep statistical understanding of large, complex datasets

• Experience in credit risk / lending or fintech domain

• Deep understanding of credit risk modeling concepts, including PD calibration, reject inference, adverse action logic, and risk segmentation

• Experience with tax and/or credit bureau data (TransUnion, Experian, Equifax) in credit model development

• Familiarity with cash flow data as alternative or complementary data sources.

• Strong business problem solving, communication and collaboration skills