Enterprise Risk Analyst
Posted on 2/10/2024
Payoneer

1,001-5,000 employees

Global digital commerce partner for borderless payments
Company Overview
Payoneer stands out as a global leader in digital commerce, offering a robust platform that simplifies cross-border payments and supports business growth in multiple currencies. The company's competitive edge lies in its ability to bypass complex international wire transfers, enabling businesses to get paid quickly and efficiently as if they were local. With a strong commitment to customer service, Payoneer provides a multi-currency account that is trusted by over 5 million users worldwide, facilitating global expansion and fostering connections with leading marketplaces.
Data & Analytics

Company Stage

N/A

Total Funding

$876.2M

Founded

2005

Headquarters

New York, New York

Growth & Insights
Headcount

6 month growth

-1%

1 year growth

1%

2 year growth

24%
Locations
New York, NY, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Agile
Python
Management
R
SQL
Java
Tableau
Scala
Apache Hive
SCRUM
Data Analysis
CategoriesNew
Software Engineering
Requirements
  • 3-5 years of risk experience, preferably in an audit, compliance, risk or related consulting experience
  • Bachelor’s Degree (or equivalent) in Finance, Economics, Physics, or related field preferred
  • Proficiency in scripting and programming languages like Java, Python, Scala, and shell scripting
  • Extensive experience in coding and crafting business requirements for algorithmic and quantitative modeling solutions
  • Familiarity with Money Services Business regulations across jurisdictions (e.g., SEC, NYDFS, FCA, CBI, MAS) as an advantage
  • Knowledge spanning technologies in big data analytics
  • Competence in handling and preparing diverse, large datasets, and specialized database architecture
Responsibilities
  • Support ERM in assessing, monitoring, and reporting on Payoneer's Risk Management Framework effectiveness
  • Utilize comprehensive knowledge of Payoneer's Risk Management Framework to address governance issues across departments, entities, and regions
  • Collaborate with ERM and business units to establish and adjust Risk Tolerances and Appetites based on data insights
  • Analyze, interpret, and present synthesized results effectively for reporting purposes
  • Evaluate existing technologies and datasets in collaboration with ERM, departments, and regions, strategizing their optimal use for analysis and decision-making
  • Develop automated processes for real-time data sourcing, ensuring data integrity for analysis
  • Contribute to building sustainable, automated reporting and dynamic dashboards for various stakeholders, including management, the VP ERM, the Board, and regulatory bodies
  • Aid in creating a dynamic Enterprise Risk Assessment, utilizing BI tools and crafting diverse dashboards across financial, technological, and operational data
  • Enhance quantitative inputs for Key Risk Indicators (KRI) and Key Performance Indicators (KPI), adapting to real-time changes in the ERM environment and data inputs
  • Interact and communicate in a highly effective, professional, and insightful manner with stakeholders
  • Exhibit and foster a strong collaboration across Payoneer control functions (e.g., Compliance, Internal Audit) to set analytics objectives and approach and work plans
  • Coordinate process and control efforts with control groups to maximize efficiency and effectiveness
  • Assist in the development of ERM reports, as well as other ad-hoc and regularly occurring reports
  • Other projects and tasks as assigned
Desired Qualifications
  • Prioritization skills handling multiple tasks concurrently
  • Collaboration across diverse teams, engaging various subject matter experts and stakeholders of different seniority levels for requirement development and data analysis
  • Adherence to regulatory data requirements and its traceability within solutions
  • Preferably skilled in Waterfall and Agile/SCRUM methodologies (with sprints)
  • Proficiency in both relational and dimensional data models within large-scale settings
  • Understanding of risk best practices
  • Profound grasp of machine learning techniques (k-NN, Naïve Bayes, SVM, Decision Forests)
  • Proficiency with Monte-Carlo or scenario analysis models and simulations
  • Practical experience utilizing statistical software (SAS, SPSS, R) for model estimation
  • Hands-on familiarity with BI tools (Tableau, Spotfire, QlikView)
  • Expertise in query languages, including SQL, Hive, and Pig
  • Experience with Governance, Risk, and Compliance (GRC) systems like Archer, Resolver, LogicGate