[Hiring] Data & Risk Strategy Enablement @WEX

Role Description

Our Team:

• The Global Risk Solutions and Strategy group is a fast-growing team optimizing risk solutions, models, and strategies.
• We are a key function in enabling WEX’s strategic objectives.
• The Team combines data science, risk expertise, technology, and a wide range of data sources to develop solutions that inform decision-making across the client lifecycle.
• Our team helps the firm identify, measure, and manage credit and fraud risk while enabling scalable, data-driven risk strategies.

As a member of the team, you will work at the intersection of data, risk strategy, data science, and technology. You will partner closely with:

• Data scientists
• Risk strategists
• Data engineers
• Technology teams
• Business stakeholders

You will ensure our teams have trusted, scalable, well-understood data and features to support analytics, modeling, and risk decisioning.

Qualifications

• 6 or more years of professional experience working with data, analytics, data science, risk, data engineering, or related disciplines, preferably within financial services or a complex data environment.
• Strong understanding of data ecosystems, including source systems, data warehouses/lakes, ETL/ELT pipelines, data transformations, and downstream analytical consumption.
• Advanced SQL skills and experience working with large, complex datasets.
• Demonstrated ability to understand complex source systems and translate business processes into data requirements and analytical datasets.
• Experience partnering with data engineering teams to build, optimize, and troubleshoot data pipelines.
• Strong understanding of data quality principles, data lineage, metadata, data governance, and data ownership.
• Experience working with feature stores, feature engineering platforms, or similar reusable data/analytics infrastructure.
• Ability to understand data science and machine learning requirements, including how features are developed, evaluated, consumed, and operationalized.
• Strong understanding of credit risk, fraud risk, payments, or other financial services risk domains.
• Strong communication and relationship-building skills, with the ability to influence teams without direct authority.
• Demonstrated ability to operate independently, identify ambiguous problems, and drive solutions across organizational boundaries.
• Strong analytical, problem-solving, and critical-thinking skills.
• Experience serving as a data or analytics subject matter expert across multiple teams or organizational functions.
• Experience owning or helping establish a feature store, feature platform, or enterprise analytics data product.
• Experience partnering on shared data platforms or capabilities across data science and engineering organizations.
• Experience developing enterprise data definitions, data standards, or data governance practices.
• Experience working with cloud data platforms and modern data architectures.
• Experience with data cataloging, lineage, data observability, or data quality platforms.
• Experience working in an environment where data science, risk strategy, and data engineering operate as highly interconnected functions.
• Experience with credit risk modeling, portfolio management, underwriting, fraud, collections, or other financial risk applications.
• Experience influencing technical roadmaps and priorities across teams without direct management authority.
• Demonstrated ability to simplify complex data environments and create reusable solutions that accelerate data science and risk strategy.

Requirements

• Serve as a trusted data and risk subject matter expert for data scientists, risk strategists, engineers, and business stakeholders.
• Develop a deep understanding of critical source systems, data structures, business processes, and data flows that support credit, fraud, and other risk strategies.
• Translate business and risk requirements into clear data requirements, helping teams identify the right data sources, transformations, features, and analytical approaches.
• Establish and promote common definitions for key risk, customer, account, transaction, and performance measures to improve consistency across analytics and decisioning.
• Identify opportunities to improve the availability, usability, quality, and scalability of data used by risk and data science teams.
• Act as a bridge between data consumers and data engineering teams, helping prioritize and communicate data requirements and technical needs.
• Partner closely with data engineering teams to design, optimize, and improve pipelines supporting risk analytics, modeling, and strategy.
• Identify bottlenecks, redundancies, data quality issues, and opportunities to improve the efficiency and reliability of existing data pipelines.
• Help establish scalable data patterns that reduce duplicated data preparation and enable data scientists and risk strategists to focus on higher-value analytical work.
• Participate in the design and review of data architecture and pipeline changes to ensure they meet downstream analytical and risk requirements.
• Proactively identify upstream data changes or source-system dependencies that could impact models, strategies, reporting, or monitoring.
• Develop strong relationships with source-system owners and downstream data consumers to improve transparency and accountability across the data ecosystem.
• Translate and support the relationship between the Risk Solutions and Strategy organization and the broader feature store ecosystem.
• Serve as the primary liaison to external teams supporting or consuming the feature store, representing the needs of data science and risk strategy.
• Support the feature store across data science, risk, and partner organizations by identifying barriers and creating practical solutions.
• Establish and promote best practices for feature development, documentation, reuse, governance, and consumption.
• Partner with teams to retain and monitor feature definitions, metadata, lineage, quality, ownership, and lifecycle management.
• Work with data scientists and engineers to identify opportunities to migrate duplicated or manually maintained features into reusable, governed feature-store assets.
• Gather feedback from internal users and translate it into enhancements, capabilities, and priorities for the feature store.
• Promote reuse of existing features and reduce unnecessary duplication across models and analytical solutions.
• Help ensure that features are discoverable, well documented, trusted, and fit for use in production risk applications.
• Establish a strong quality mindset around data used for risk decisioning and model development.
• Investigate and coordinate resolution of data issues across source systems, pipelines, and downstream consumers.
• Partner with data governance and technology teams to improve data lineage, ownership, documentation, and controls.
• Identify gaps in data definitions and work across teams to establish consistent business and technical definitions.
• Proactively communicate data risks, dependencies, and limitations that could affect analytical or risk outcomes.

Benefits

• Generous paid time off and paid volunteering time.
• Health, dental, and vision insurances.
• Retirement savings plan.
• Health savings account.
• Flexible spending accounts.
• Life insurance and disability insurance.
• Tuition reimbursement.
• Comprehensive and market competitive benefits designed to support personal and professional well-being.

Company Description

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.