Senior Credit Data Scientist

Job not on LinkedIn

🔥 40 minutes ago

🇺🇸 United States – Remote

💵 $140k - $165.4k / year

⏰ Full Time

🟠 Senior

📊 Data Scientist

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 0%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

WEX

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 1983

🏥 Healthcare

📦 Logistics

✈️ Travel

💰 $310M Post-IPO Debt on 2020-06

Healthcare • Logistics • Travel

WEX is a global commerce platform specializing in various business solutions to address operational challenges. They provide services in managing and mobilizing fleets with their fuel card systems, offering comprehensive fleet management and analytics. Additionally, they focus on business payments solutions that streamline processes across industries, enhancing efficiency and security. WEX is also involved in employee benefits administration, helping organizations effectively manage health and reimbursement accounts. Their diverse range of services caters to numerous sectors, emphasizing innovation, sustainability, and effective solutions for business growth.

📋 Description

• Partner with stakeholders to understand fraud risk management requirements and translate them into data-driven solutions • Measure and monitor fraud risk across the firm’s products and services • Identify and communicate challenges, opportunities, and risks throughout the model development and deployment lifecycle • Leverage machine learning, artificial intelligence, and statistical methods to design scalable and automated risk modeling solutions • Develop and review code and automated processes to extract fraud risk patterns from application and transaction data, behavioral patterns, and other risk indicators • Monitor emerging machine learning trends and identify opportunities to improve processes • Mentor and support junior data scientists • Deliver hypothesis- and objective-driven analytics to inform business decisions and metrics • Collaborate with stakeholders and tailor analytical deliverables to maximize impact • Drive analytics from end-to-end experiences through production with measurable impact • Improve team best practices and processes • Ensure data and analytical quality from project inception • Learn, use, and teach new technologies as needed

🎯 Requirements

• 4 or more years of professional experience in data science, machine learning, and artificial intelligence, focused on fraud risk management in financial services • Master’s or Ph.D. degree in a quantitative field such as Mathematics, Statistics, Data Science, Operations Research, or Computer Science • Strong knowledge of fraud risk-drivers in small and medium sized businesses, public firms, and private firms • Advanced knowledge of SQL and experience creating and managing large datasets • Advanced knowledge of Python or R and common data science libraries such as lightgbm, scikit-learn, and pandas • Deep understanding of model deployment requirements for scalable solutions and real-time feature stores • Deep expertise in statistical and machine learning techniques, including modeling, testing, inference, sampling methods, supervised learning, and unsupervised learning • Strong communication and presentation skills • Ability to work collaboratively and independently in a self-starting manner • Evidence of creative problem solving, critical thinking, and continual learning in credit risk management • Prior experience mentoring data scientists • Prior experience building underwriting and behavioral models • Knowledge of external intelligence sources, including LexisNexis, Socure, and Dun and Bradstreet • Experience using cloud environments such as AWS Sagemaker • Experience with end-to-end machine learning systems and MLOps frameworks • AI tool experience preferred, 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 • Quarterly or annual bonus eligibility for non-sales roles