Freelance Credit Risk Data Scientist – Machine Learning for Lending Products

ThreatXIntel; India; On-site; INR 1,000,000 - 1,500,000; Part time

Job summary

A cybersecurity startup is seeking a Credit Risk Data Scientist to design and implement advanced machine learning models for predicting credit risk in lending products. This part-time, mid-senior level position requires strong skills in Python and SQL, along with experience in credit risk modeling. The ideal candidate will collaborate with product and risk teams to align model outcomes with business strategies.

Qualifications

• 2+ years of professional experience in Data Science or Machine Learning, focusing on credit risk modeling.
• Experienced with large-scale datasets, feature engineering, and model training.
• Familiarity with credit bureau data and alternative credit data sources.

Responsibilities

• Design, build, evaluate, and defend machine learning models for predicting credit risk.
• Collaborate with product and risk teams to align model outcomes with business goals.
• Deploy and monitor models in production environments.

Skills

Python libraries (e.g., scikit-learn, XGBoost, LightGBM, pandas, numpy)

Strong proficiency in SQL

Communication and collaboration skills

Problem-solving skills

Education

Bachelor’s or Master’s degree in Mathematics, Statistics, Computer Science, or a related field

Tools

Python

SQL

Job description

Freelance Credit Risk Data Scientist – Machine Learning for Lending Products

ThreatXIntel is a startup cyber security company dedicated to protecting businesses and organizations from evolving cyber threats. We specialize in providing tailored, cost-effective solutions in areas such as cloud security, web and mobile security testing, DevSecOps, and more. Our proactive approach ensures continuous monitoring and testing to identify vulnerabilities before they can be exploited. With a mission to deliver high-quality services, ThreatXIntel empowers businesses of all sizes to safeguard their digital assets effectively. Our team fosters peace of mind, allowing clients to focus on achieving their growth goals.

Role Description

We are seeking an experienced Credit Risk Data Scientist to design and implement advanced machine learning models for predicting credit risk across multiple short-term lending products, including tax refund advances, Buy Now Pay Later (BNPL), and installment loans. This is a hands‑on, data‑driven role requiring both technical depth and business acumen to drive impactful lending decisions.

Key Responsibilities

• Design, build, evaluate, and defend machine learning models to predict credit risk across various lending products
• Collaborate with product and risk teams to align model outcomes with business goals and lending strategies
• Develop data pipelines for feature engineering, model training, scoring, and performance tracking using Python and SQL
• Deploy and monitor models in production environments, collaborating with engineering teams and other data scientists to ensure scalability and performance
• Work with stakeholders to formulate credit policies driven by insights from machine learning models
• Track and evaluate model performance using metrics like AUC, KS, Gini, and stability measures like PSI and CSI
• Ensure model fairness, interpretability, and compliance with regulatory frameworks (e.g., FCRA, ECOA)
• Maintain awareness of data privacy and ethical considerations related to credit risk models

Required Skills and Experience

• Bachelor’s or Master’s degree in Mathematics, Statistics, Computer Science, or a related field
• 2+ years of professional experience in Data Science or Machine Learning, with a focus on credit risk modeling
• Hands‑on experience with Python libraries (e.g., scikit-learn, XGBoost, LightGBM, pandas, numpy)
• Strong proficiency in SQL for data extraction, transformation, and analysis
• Experience working with tree-based models, regression, time series, causal inference, and clustering techniques
• Proven ability to work with large-scale datasets, feature engineering, and model training
• Experience in credit risk modeling or in the fintech domain
• Deep knowledge of PD calibration, reject inference, adverse action logic, and risk segmentation
• Familiarity with credit bureau data (e.g., TransUnion, Experian, Equifax) and alternative credit data sources like cash flow data
• Strong communication, collaboration, and problem-solving skills to work with business and technical teams

Preferred Experience

• Prior experience in short-term lending, BNPL, or tax advance products
• Exposure to credit risk model governance and regulatory compliance
• Familiarity with automated model governance frameworks for monitoring and ensuring compliance in credit risk models

Seniority level: Mid‑Senior level

Employment type: Part‑time

Job function: Engineering and Information Technology
Industries: Computer and Network Security