VP, Enterprise Fraud Analytics & Reporting

Synchrony•Orlando, FL

21h•Hybrid

About The Position

This role is responsible for owning and stewarding key fraud and credit data sources used for analytics, reporting, and operational decisioning. The position involves designing, developing, and maintaining fraud analytics solutions and data processes using SAS. It also includes building and optimizing data pipelines, queries, and analytical datasets to enable fraud detection, investigation, and reporting. The role requires demonstrated experience in scheduling, monitoring, and troubleshooting production jobs and batch processes, as well as monitoring and validating critical feeds, performing reconciliations, and driving resolution of data issues. Establishing and maintaining controls for timely data availability and partnering with Data Engineering/Technology teams for data definitions and documentation are key. The role also supports large-scale migrations and performs other assigned duties. Synchrony offers flexibility in its way of working, allowing employees the option to work from home near a Hub or come into an office. Commuting to the nearest Hub (virtual or physical) is required for in-person engagement activities like meetings, training, and culture events. Field Sales and some Commercial team roles may have varied location requirements.

Requirements

7-10 years hands on experience building and managing comprehensive data infrastructure serving a wide base of constituents focusing on Management Reporting, Strategy and Analysis, and Operational Performance Management.
5+ years of hands-on SAS experience.
Strong SQL skills and experience working with large datasets in enterprise environments.
Minimum 5+ years of experience in Financial Services, with a focus on Fraud detection, prevention, and investigation.
Demonstrated experience working in a fast-paced environment with shifting priorities and tight timelines.
Ability to design, support, and optimize complex end-to-end flows (multi-step dependencies, upstream/downstream integrations, SLA management, reruns/recovery procedures).
Strong understanding of KPI’s and ability to tell effective stories connecting KPI trends to business drivers.
Advanced dashboarding skills and experience in using Tableau or Sas Visual Analytics
Ability and flexibility to travel for business as required
You must be 18 years or older
You must have a high school diploma or equivalent
You must be willing to take a drug test, submit to a background investigation and submit fingerprints as part of the onboarding process
You must be able to satisfy the requirements of Section 19 of the Federal Deposit Insurance Act.
Legal authorization to work in the U.S. is required.
We will not sponsor individuals for employment visas, now or in the future, for this job opening.

Nice To Haves

Bachelor's degree a in STEM field such as Mathematics, Statistics, Analytics, or any Quantitative field.
Ability to lead projects by influencing and aligning team members who are not direct reports.
Proven experience with large-scale migrations, conversions, or modernization efforts (data, platforms, or analytics tooling).
Experience with SAS Viya Cloud Environment
Familiarity with cloud data platforms and modern data ecosystems (tooling varies by environment).
Proven experience using Copilot and other generative AI tools and solutions to improve productivity and outcomes.
Proven hands-on experience utilizing open-source tools such as R and Python.
Ability to effectively delegate projects, project negotiation skills and skills to coach junior members on the team.

Responsibilities

Own and steward key fraud and credit data sources used for analytics, reporting, and operational decisioning—ensuring datasets are accurate, complete, and delivered on time in alignment with SLAs.
Design, develop, and maintain fraud analytics solutions and data processes using SAS (batch and/or real-time workflows, as applicable).
Build and optimize data pipelines, queries, and analytical datasets to enable fraud detection, investigation, and reporting.
Demonstrated experience scheduling, monitoring, and troubleshooting production jobs and batch processes (e.g., via enterprise schedulers such as Flow Manager, Stonebranch, Autosys, or similar tools).
Monitor and validate critical feeds (upstream/downstream), perform reconciliations and data quality checks, and drive resolution of data issues impacting fraud and credit performance.
Establish and maintain controls to ensure timely availability of recurring datasets (daily/weekly/monthly), including proactive outage prevention, alerting, and rapid triage during incidents.
Partner with Data Engineering/Technology teams to maintain data definitions, mappings, lineage, and documentation for high-impact fraud/credit datasets.
Support large-scale migrations (e.g., platform modernization, data warehouse migrations, tool upgrades), including requirements gathering, data validation, parallel testing, and production cutover support.
Perform other duties and/or special projects as assigned.