Sr Credit Data Scientist

WEX Inc.; Maine; Ibrido; USD 140.000 - 165.000; Tempo pieno

Vantaggi offerti da questo lavoro

Health insurance

Dental insurance

Vision insurance

Retirement savings plan

Paid time off

Health savings account

Flexible spending accounts

Life insurance

Disability insurance

Tuition reimbursement

and more

Descrizione del lavoro

WEX Inc. is seeking a data scientist to partner with stakeholders and translate fraud risk requirements into scalable, data-driven solutions. You will develop, validate, and deploy models to monitor fraud across products, leveraging machine learning and statistical methods on large transaction data.

The role emphasizes collaboration, continuous learning, and mentoring junior data scientists while delivering measurable business impact through rigorous analytics and production-ready pipelines.

Competenze

• 4+ years of professional experience in data science focusing on fraud risk management.
• Master's or Ph.D. in Mathematics, Statistics, Data Science, OR related field.
• Knowledge of fraud risk drivers across various firm sizes and data sources.
• Advanced SQL for large datasets and data extraction.
• Advanced Python or R and common data science libraries.
• Experience deploying models and real-time feature stores.
• Strong communication and presentation skills with business impact.
• Self-starting, collaborative with a continual learning mindset.

Mansioni

• Partner with stakeholders to translate fraud risk requirements into data-driven solutions.
• Develop, test, and deploy fraud risk models across products and services.
• Extract patterns from large-scale data and maintain automated processes.
• Mentor junior data scientists and share best practices.
• Stay current with ML trends and integrate new tools when beneficial.

Conoscenze

Fraud risk

SQL

Python

Data science

Machine learning

Communication

MLOps

Formazione

Master's or Ph.D. in quantitative field

Strumenti

LightGBM

scikit-learn

Pandas

Descrizione del lavoro

The Global Risk Solutions and Strategy group is a fast-growing team optimizing risk solutions and models, and we are a key function to help enable WEX's strategic objectives. The Risk Solutions Team employs data science methodologies (machine learning and statistical frameworks), a wide suite of data types, and modern technologies to develop solutions to inform decision making. Our team helps the firm identify and measure credit and fraud risk to proactively manage the risk throughout the client's life-cycle. As such, you will not only be working with the latest data and machine learning technologies and algorithms, you will be working in a dynamic environment alongside our stakeholders and domain experts to build models and drive better decision-making.

About the Team/Role

Partner with stakeholders to understand fraud risk management requirements and translate them into data-driven solutions to measure and monitor fraud risk across the firm's products and services. Proactively identify and communicate challenges, opportunities, and risks associated with end-to-end model development and deployment life-cycle to ensure timely completion of the entire product. Leverage advanced machine learning, artificial intelligence, and statistical methods and technologies to design flexible, scalable, and automated risk modeling solutions. Develop and review code and automated processes to extract fraud risk patterns from large scale application and transaction data, behavioral patterns, and other risk indicators. Keep abreast with emerging trends in machine learning and identify opportunities to leverage new tools to solve problems and improve processes. Mentor and support junior data scientists, sharing knowledge and best practices to elevate the data science practice at WEX.

How you'll make an impact

• Insights Driven: Clear hypothesis and objective driven analytics that help drive our business decisions and ongoing metrics
• Stakeholder Aligned: Understand the needs and audience for deliverables with a succinct and tailored message to maximize impact
• Results Focused: Rigorous focus on how analytics drive the end to end experiences with clear path to production and measurable impact
• Dynamic Collaboration: Drive continual improvement of our team best practices and processes to power collaboration
• Quality Mindset: Trust in our findings is critical so data and analytic quality is understood and accounted for from the beginning
• Curiosity and Learning: Learn new technologies and collaborate and teach others how to use them as necessary.

Experience You’ll Bring

• 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, Computer Science.
• Strong knowledge of fraud risk-drivers in small and medium sized businesses, public firms, and private firms, including data typically 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 to organize and extract useful information.
• Advanced knowledge of Python or R and experience with common data science libraries such as lightgbm, scikit-learn, pandas, etc..
• 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 an ability to relate complex analytics findings to business outcomes.
• Adaptable and comfortable working collaboratively and independently in a self-starting manner.
• Evidence of creative problem solving, critical thinking and a continual learning mindset in credit risk management.

How you will stand out

• Prior experience mentoring experience of data scientists
• Prior roles responsible for building underwriting and behavioral models.
• Knowledge of external intelligence sources, including third-party data providers e.g. LexisNexis, Socure, Dun and Bradstreet
• Experience using cloud environments to develop advanced models, such as AWS Sagemaker
• Experience with end-to-end machine learning systems and MLOps framework AI Tool Experience
• Preferred -- Gemini, ChatGPT, Similar

Compensation and Benefits

Pay Range: $140,000.00 - $165,400.00

• health insurance
• dental insurance
• vision insurance
• retirement savings plan
• paid time off
• health savings account
• flexible spending accounts
• life insurance
• disability insurance
• tuition reimbursement
• and more

WEX is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex, race, color, age, national origin, religion, sexual orientation, gender identity, protected veteran status, disability or other protected status.

WEX promotes a drug-free workplace. Qualified individuals with a disability have the right to request a reasonable accommodation. If you require a reasonable accommodation as a result of your disability at any point in the job application process, please submit your request through our Reasonable Accommodation Request Form. This form is for accommodation requests only and cannot be used to inquire about the status of applications.

If you’re looking for a growing career - come be part of WEX today.