Data Scientist

Join to apply for the Data Scientist role at Noxx We are building an advanced credit scoring system for international newcomers who lack domestic credit history. Our mission is to combine financial behavior data, banking transactions, demographic information, and behavioral patterns to create a fair and practical credit assessment model. To accelerate this initiative, we are seeking a high-level Data Scientist with deep expertise in statistics, machine learning, and financial analytics to join us on a part-time basis. You will work hands‑on across the full modeling pipeline—from data preparation to production‑ready model design—focusing on both predictive accuracy and explainability. Key Responsibilities 1. Data Preparation & Analysis Clean, validate, and structure financial transaction data, demographic data, and behavioral data Handle missing values, outliers, and data inconsistencies Construct training datasets based on defined delinquency and default labels Design features that reflect the unique financial patterns of international newcomers Build time‑series and behavior‑based aggregated features Implement reproducible feature generation using Python and SQL Develop baseline statistical models (e.g., Logistic Regression, Ordered Logistic Regression) Build and refine machine learning models (Random Forest, Gradient Boosting, Neural Networks, etc.) Evaluate models using AUC, KS, ROC, calibration metrics, and other indicators Conduct model interpretation using SHAP or other explainability tools 4. Fairness & Explainability Document modeling assumptions, limitations, and risk considerations Support the development of credit policy guidelines 5. Production Integration Draft specifications for integrating models into APIs or batch scoring systems Contribute to model monitoring, retraining pipelines, and drift detection Create dashboards and BI outputs using Tableau or similar tools Required Qualifications Candidates must meet all of the following requirements: Statistical & Analytical Skills Graduate‑level understanding of statistics, probability, and linear models Hands‑on experience with binary classification model development Programming Strong proficiency in Python for data analysis Solid SQL experience for data extraction and manipulation Experience using GitHub for code management and collaboration Domain Knowledge Practical experience in financial analytics, credit risk, insurance, investments, or ESG‑related data work Ability to explain model findings and translate insights into business actions Communication Japanese: business level (documentation, internal meetings) English: ability to read technical materials (verbal communication a plus) Preferred Qualifications 3 year + Experience developing credit risk or scoring models (banking, credit card, fintech, etc.) Experience analyzing large‑scale datasets (100GB+) or healthcare/financial big data Experience with AWS (S3, Athena, Lambda, SageMaker, etc.) Experience with VBA, R, or MATLAB Background in risk modeling, derivatives, or project finance Practical experience in at least one of the following: Time Series Analysis Bayesian Statistics Unsupervised Learning Who We’re Looking For Strong motivation to solve the social challenge of “credit invisibility” among newcomers Commitment to fairness, transparency, and responsible AI Comfortable working in a zero‑to‑one product environment Able to collaborate across product, engineering, and business teams Work Conditions Expected workload: 10–20 hours per week Weekly online meetings: 1–2 sessions Contract: initial 3‑month term with possible extension Seniority level Mid‑Senior level Employment type Part‑time Job function Engineering and Information Technology Industries Technology, Information and Internet #J-18808-Ljbffr