Data Scientist Specialist (Lending)

Accountabilities:

• Develop and deploy real-time scoring models to assess credit and transaction risk with high accuracy and scalability.

• Build predictive machine learning models using internal and external data to optimize onboarding and reduce credit losses.

• Evolve static rule-based systems into dynamic, graph-based decision engines for more adaptive risk management.

• Analyze large-scale behavioral, transactional, and demographic datasets to identify patterns and improve risk strategies.

• Design and implement advanced solutions such as fingerprinting and geolocation-based tracking to enhance fraud and risk detection.

• Monitor, evaluate, and improve the performance, stability, and accuracy of credit and risk models in production environments.

• Lead technical initiatives, mentor team members, and contribute to best practices in data science and machine learning engineering.

• Support the adoption of modern data platforms and tools, including Databricks and data catalog systems, to improve scalability and efficiency.

Requirements:

• Strong proficiency in Python, SQL, and Spark, with experience using libraries such as Pandas, NumPy, Scikit-learn, and Matplotlib.

• Solid experience building and deploying machine learning models, including classification, regression, clustering, and feature engineering.

• Deep understanding of model evaluation techniques such as AUC, KS, precision, recall, and statistical significance testing.

• Strong background in A/B testing, experimental design, and statistical analysis.

• Experience working with large-scale datasets and writing optimized SQL queries for performance.

• Knowledge of model interpretability techniques such as SHAP, weight of evidence, and bivariate analysis.

• Familiarity with cloud and data platforms such as Databricks, AWS, or Azure, and version control tools like Git.

• Strong problem-solving mindset with the ability to translate complex technical results into actionable business insights.

• Excellent communication and collaboration skills in cross-functional and technical environments.

• Nice to have: experience with PySpark, MLOps, production model monitoring, and fintech or credit-related data systems.

Benefits:

• Fully remote role, allowing you to work from anywhere in the world.

• Competitive and market-aligned compensation package.

• Home office allowance provided via monthly deposit.

• Comprehensive health and dental insurance with no co-payment.

• Life insurance coverage.

• Flexible meal allowance.

• Fitness and wellness support through TotalPass membership.

• Strong culture of autonomy, ownership, and impact-driven work.

• Opportunity to work in a high-scale fintech environment serving millions of users.

How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

#LI-CL1