Senior Fraud Data Scientist

🕒 October 16

🇺🇸 United States – Remote

💵 $140k - $165.4k / year

⏰ Full Time

🟠 Senior

📊 Data Scientist

🦅 H1B Visa Sponsor

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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 across the model development and deployment lifecycle • Apply advanced machine learning, artificial intelligence, and statistical methods to design flexible, scalable, automated risk modeling solutions • Develop and review code and automated processes to extract fraud risk patterns from application, transaction, behavioral, and other risk data • Monitor emerging machine learning trends and identify opportunities to improve processes • Mentor and support junior data scientists • Deliver hypothesis- and objective-driven analytics that inform business decisions and ongoing metrics • Create stakeholder-aligned deliverables with succinct, tailored messaging • Drive analytics from end-to-end experiences through production and measurable impact • Improve team best practices and processes to support collaboration • Ensure data and analytic quality from the beginning of projects • Learn, use, and teach new technologies as needed

🎯 Requirements

• 4 or more years of professional experience in data science, machine learning, and artificial intelligence, with a focus on fraud risk management in underwriting, behavioral surveillance, and loss prevention in the financial services industry • 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 • Knowledge of data used in fraud risk management from external credit bureaus and internal risk management processes • 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 and inference, sampling methods, supervised and unsupervised learning • Strong communication and presentation skills with ability to relate complex analytics findings to business outcomes • 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 such as 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 or ChatGPT

🏖️ Benefits

• Health, dental and vision insurances • 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

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