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Senior Data Scientist
| Company | Wex |
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| Location | Portland, ME, USA |
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| Salary | $135000 – $180000 |
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| Type | Full-Time |
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| Degrees | Master’s, PhD |
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| Experience Level | Senior |
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Requirements
- 3+ years of professional experience in data science, machine learning, or artificial intelligence, with a strong focus on fraud detection, including transaction and application monitoring in the fintech/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 models, including supervised and unsupervised learning techniques, and behavioral analysis.
- 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..
- Understanding of model deployment requirements for scalable solutions.
- 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 fraud prevention.
Responsibilities
- Partner with stakeholders to understand fraud risk challenges and translate them into data-driven solutions to measure and monitor fraud risk across the firm’s products and services.
- Leverage advanced machine learning, Artificial Intelligence, and statistical methods and technologies to design flexible, scalable, and automated risk modeling solutions.
- Develop code and automated processes to extract fraud patterns from large scale transactional data, device intelligence, behavioural analytics, and other risk indicators.
- Synthesize findings into actionable insights and articulate them to the appropriate stakeholders.
- Collaborate closely with fraud strategy, risk operations, and technology teams to integrate fraud model solutions both in rule-based systems and cloud infrastructures.
- Mentor and support junior data scientists, sharing knowledge and best practices to elevate the data science practice at WEX.
- Proactively identify and communicate challenges, opportunities, and risks associated with project work to ensure timely completion of the entire product.
Preferred Qualifications
- Prior experience building application and transaction fraud detection models.
- Knowledge of external fraud intelligence sources, including third-party data providers e.g. LexisNexis.
- Knowledge of fraud rules-based systems and how machine learning can complement rule-based decisioning.
- Experience using cloud environments to develop advanced models, such as AWS Sagemaker.
- Experience with end–to-end machine learning systems and MLOps framework.
- Experience with LexisNexis products.
