Data Scientist

Who We Are

Our Team: 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 Data Science team uses a variety of advanced methodologies (including 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 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.

Our Company: WEX is a fast-growing multinational payments company based in beautiful Portland, Maine. WEX headquarters is situated in the heart of Portland amongst some of the best restaurants in the country and overlooking the ocean and lighthouses. When you are here, you know you are in Maine. We have generous paid time off and paid volunteering time, not to mention great benefits and a culture that values diversity and inclusion.

About the Team/Role

• Partner with stakeholders to understand their needs and translate them into data-driven solutions to measure and monitor risk across the firm’s products and services.

• Leverage a broad spectrum of advanced statistical and machine learning methods and technologies to design flexible, scalable, and automated modeling solutions.

• Develop code and automated processes to combine and transform large volumes of data from disparate sources, to extract informative patterns.

• Keep abreast with emerging trends in machine learning and identify opportunities to leverage new tools to solve problems and improve processes

• Synthesize findings into actionable insights and articulate them to the appropriate stakeholders.

• 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

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 teambest 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:

• 3+ years of hands-on experience in data science, machine learning, or artificial intelligence, preferably in fintech/ financial services industry

• Excellent analytical, creative problem-solving, and critical thinking skills, with the ability to tackle complex challenges and deliver innovative solutions.

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

• 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 data science libraries such as lightgbm, scikit-learn, pandas, numpy etc.

• 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

How you will stand out:

• 2+ years experience building machine learning risk models in payment processing

• Extensive knowledge of data attributes and coverage of risk-factors in external bureau data for small business.

• Experience using cloud environments to develop advanced models, such as AWS Sagemaker

• Experience with end–to-end ML lifecycle and MLOps frameworks such as Docker, CI/CD, Airflow.

Key Words

Data Science, Machine Learning, Statistical Learning, Artificial Intelligence, Credit Risk, Fraud, Finance