Senior Data Analyst

Platform Related

• Support Active Users of MRM with questions they have on the system and processes utilized in the tool.
• Collaborate with stakeholders to discuss requirements, upcoming projects, timelines and issues.
• Develop Requirements for System Enhancements by working with cross-functional teams requiring the change and writing user stories.
• Communicate with IT to implement changes through an iterative agile process.
• Manage Technology Releases using agile methodology by utilizing JIRA and prioritizing, grooming enhancements.
• Manage and Complete UAT and Production Validation including writing and executing test scripts.
• Provide system accesses to users.
• Maintain Features Document.
• Help manage Ongoing and Annual User Training and Documentation.

Invoice and Accrual Management

• Manage the accruals processes.
• Create and analyze reports to ensure accuracy of data.
• Manage all invoice processing in P2P and associated reclassing in MRM.
• Track and manage vendor spend.
• Manage project code processes.

What You Will Need

• Working knowledge or experience with one or more of the following tools: SQL, R, Python, Scala, Spark or similar programming language.
• 1-2 years of experience in Linux, shell scripting and/or similar scripting languages for automation.
• Ability to demonstrate critical thinking and enthusiasm for translating data into actionable insight to generate consistently accurate and useful analysis and models.
• Bachelor’s Degree in a quantitative field (Applied Mathematics, Applied Statistics, Economics, or Computer Science) or related degree programs and 2 years of relevant work experience.
• 2 years of relevant work experience.
• Ability to work independently when given detailed specification and instruction.
• At least 1 year of experience in statistical modeling techniques to conduct forecasting and other predictive modeling services using R, Python, Scala, Spark/pySpark.
• Experience with Tableau, Microsoft Excel, and Power Point.

What Will Set You Apart

• Knowledge of Deep Learning, Neural Network based on modeling frameworks a plus.
• Experience in a financial services industry.
• Familiarity with cloud environments (e.g. AWS, Google Cloud Platform, Azure etc.).