Senior Credit Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Collaborate with stakeholders to grasp the requirements for managing fraud risk and convert them into data-driven solutions.

• Assess and track fraud risk across the organization’s products and services.

• Identify and relay challenges, opportunities, and risks throughout the lifecycle of model development and deployment.

• Utilize machine learning, artificial intelligence, and statistical methods to create scalable and automated risk modeling solutions.

• Create and review code and automated processes to extract patterns of fraud risk from application and transaction data, behavioral indicators, and other risk signals.

• Stay updated on emerging trends in machine learning and pinpoint opportunities for process enhancements.

• Provide mentorship and support to junior data scientists.

• Conduct hypothesis- and objective-driven analytics to guide business decisions and metrics.

• Work alongside stakeholders and customize analytical deliverables to maximize their impact.

• Manage analytics from end-to-end processes through production with measurable results.

• Enhance team best practices and workflows.

• Guarantee data and analytical quality from the beginning of projects.

• Acquire, utilize, and teach new technologies as necessary.

⛳️ Requirements

• A minimum of 4 years of professional experience in data science, machine learning, and artificial intelligence, specifically within fraud risk management in the financial services sector.

• A Master’s or Ph.D. degree in a quantitative field such as Mathematics, Statistics, Data Science, Operations Research, or Computer Science.

• Comprehensive knowledge of fraud risk drivers in small to medium-sized businesses, as well as public and private firms.

• Advanced proficiency in SQL along with experience in creating and managing extensive datasets.

• Proficient in Python or R and familiar with common data science libraries such as lightgbm, scikit-learn, and pandas.

• In-depth understanding of model deployment requirements for scalable solutions and real-time feature stores.

• Extensive expertise in statistical and machine learning techniques, including modeling, testing, inference, sampling methods, supervised learning, and unsupervised learning.

• Excellent communication and presentation skills.

• Capability to work both collaboratively and independently in a self-starting manner.

• Proven record of creative problem solving, critical thinking, and continuous learning in credit risk management.

• Prior experience in mentoring data scientists.

• Experience in developing underwriting and behavioral models.

• Acquainted with external intelligence sources like LexisNexis, Socure, and Dun and Bradstreet.

• Familiarity with cloud environments such as AWS Sagemaker.

• Experience with complete machine learning systems and MLOps frameworks.

• Preferred experience with AI tools, including Gemini, ChatGPT, or similar.

🏝️ Benefits

• Health insurance

• Dental insurance

• Vision insurance

• Retirement savings plan

• Paid time off

• Health savings account

• Flexible spending accounts

• Life insurance

• Disability insurance

• Tuition reimbursement

• Eligibility for quarterly or annual bonuses for non-sales roles