Position: Sr. Data Analyst
Location: 320 S Canal St. Chicago, IL - Hybrid - training to start will be in office Monday and Wednesday. Flexible after training wraps up
Duration: 9 months, extensions possible, FTE possible based on performance
Pay: $35-50/hr
Start Date: March 3rd
Notes: One and done interview- 45 minutes
Hours: 8-4 or 9-5
Must Haves:
• 4+ years of Data Analytics experience- specifically with data clean up and data migration
• Previous banking experience required
• Bachelor's degree
• Intermediate Programming, Query, Modeling and Analytical Tool skills (SQL)
• Comfortable in a fast-paced and ambiguous environment, and is a quick learner
• Ability to work independently with limited supervision
• Strong relationship-building and cross-functional collaboration skills
• Excellent critical thinking/analytical/problem solving and organizational skills; ability to analyze issues/requests and determine next steps
• General understanding of data and how it’s used to inform business decisions; data-driven decision-making
Plusses:
• Python/SAS a nice to have
• Background in Lending or Operations an asset.
Day to Day:
The selected candidate will be supporting the data analysis and data clean-up needs for the North American Commercial Bank. the US Emerging Middle Market (EMM), US Lower Middle Market (LMM), and the Canadian Mid-Market (MM). They will work to support a data cleanup project in the initial stages brought about by the BOTW merge. The selected candidate will have a previous background in data clean-up and data migration projects, strong critical thinking skills, and previous banking experience.
Role Responsibilities Include (but are not limited to):
• Review duplicated data sources and cleanse based on given protocols.
• Breaks down strategic problems, and analyses data and information to provide insights and recommendations.
• Provides value through insights, reporting and data visualization techniques. Selects, configures and implements analytics solutions for consistency and repeatability.
• Researches and applies continuous improvement in datasets by identifying trends and patterns to transform raw data into actionable business insights.
• Exercises judgment to identify, diagnose, and solve problems within given rules.
• Works independently and regularly handles non-routine situations.
• Broader work or accountabilities may be assigned as needed.
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