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Remediation Analytics Specialist

This role is for a Remediation Analytics Specialist on a W2 contract for "X months" at a pay rate of "$X/hour". Key skills include SQL, SAS, data analytics, and machine learning. Experience with business risk and restitution processes is preferred.
🌎 - Country
United States
💱 - Currency
$ USD
💰 - Day rate
Unknown
Unknown
🗓️ - Date discovered
February 11, 2025
🕒 - Project duration
Unknown
🏝️ - Location type
Unknown
📄 - Contract type
W2 Contractor
🔒 - Security clearance
Unknown
📍 - Location detailed
Deerfield, IL
🧠 - Skills detailed
#Datasets #Data Analysis #ML (Machine Learning) #SQL (Structured Query Language) #Customer Segmentation #SAS
Role description
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Our client is currently seeking a Data Analyst for their Remediation Analytics team.

W2 Only

Remediation Analytics team, specializing in calculating refund amounts for card customers affected by errors. This role involves heavy data analytics and requires collaboration with business partners to understand various business areas, issues, and pertinent data. You will work closely with Business Risk to determine action plans for each restitution and calculate necessary refunds.

Responsibilities:
• Execute analytical initiatives in collaboration with management.
• Solve business problems using segmentation, optimization, advanced analytics, and machine learning.
• Create reports and dashboards to monitor performance metrics and provide insights.
• Lead the development and implementation of advanced analytics, including customer segmentation, optimization, prescriptive analytics, and machine learning algorithms.
• Serve as a subject matter expert on statistical analysis, experimental design, analysis methodology, modeling, and financial impact analysis.
• Develop and automate reports, build and prototype dashboards to provide insights at scale.

Qualifications:
• Strong proficiency in SQL and SAS.
• Excellent communication skills.
• Detail-oriented with a strong focus on accuracy.
• Experience in data analytics and working with large datasets.
• Ability to collaborate effectively with cross-functional teams.
• Strong problem-solving skills and ability to manage multiple priorities.

Preferred Qualifications:
• Experience with machine learning and advanced analytics techniques.
• Familiarity with business risk and restitution processes.