Analyze, clean, validate, and transform client-provided data from diverse sources and formats before system upload
Execute SQL queries and Python scripts to process, reconcile, and validate large transactional datasets
Investigate data quality issues, exceptions, and inconsistencies to present findings to project managers for client resolution
Collaborate with internal teams and external stakeholders to resolve data-related issues and ensure accuracy
Review project manager requests to determine data processing requirements and deliver processed datasets
Recommend and implement process improvements that increase accuracy, consistency, and operational efficiency

Bachelor's degree in Computer Science, Statistics, Data Analytics, Mathematics, Business, or related field
Proven experience as a data analyst working with structured datasets, particularly large record-based or transactional data
Proficiency in Python (preferably pandas) for data cleaning, transformation, validation, and reconciliation
Strong SQL skills for data extraction, joining, filtering, aggregation, and validation
Demonstrated ability to identify and resolve data quality issues including duplicates, missing values, and record inconsistencies

Simpluris, Inc.

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