Signature IT World Inc

Data Analyst with Payment Card Industry

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Data Analyst position in the Payment Card Industry, based in Whippany, NJ, on a contract basis. Requires expertise in SQL, Python or R, and data visualization tools. Experience in fintech or payments and PCI compliance knowledge is essential.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
Unknown
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πŸ—“οΈ - Date
May 1, 2026
πŸ•’ - Duration
Unknown
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🏝️ - Location
On-site
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πŸ“„ - Contract
Unknown
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
Whippany, NJ
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🧠 - Skills detailed
#BigQuery #Security #PostgreSQL #BI (Business Intelligence) #R #Compliance #Visualization #Tableau #PCI (Payment Card Industry) #Microsoft Power BI #Data Analysis #Databases #Risk Analysis #MySQL #SQL (Structured Query Language) #Computer Science #Statistics #Pivot Tables #Python #Datasets
Role description
Job Title: Data Analyst – Payment Card Industry (PCI) Location: Whippany NJ Type: Contract Role Overview We are looking for a Data Analyst with experience in the payment card ecosystem to analyze transaction data, detect trends, ensure compliance, and support business decisions. The role involves working with large datasets related to card payments, fraud detection, customer behavior, and regulatory compliance. Key Responsibilities β€’ Analyze large volumes of card transaction data (credit/debit, POS, online payments) β€’ Identify trends, anomalies, and patterns in payment behavior β€’ Support fraud detection and risk analysis β€’ Generate dashboards and reports for stakeholders β€’ Ensure compliance with PCI DSS requirements β€’ Work with payment networks like Visa Inc., Mastercard, and American Express β€’ Collaborate with product, risk, and engineering teams β€’ Perform data validation and quality checks β€’ Support chargeback and dispute analysis β€’ Build predictive models for customer and fraud insights (optional/advanced) Required Skills Technical Skills β€’ SQL (advanced queries, joins, optimization) β€’ Python or R for data analysis β€’ Data visualization tools (Tableau, Power BI) β€’ Excel (advanced functions, pivot tables) β€’ Understanding of databases (MySQL, PostgreSQL, BigQuery, etc.) Domain Knowledge β€’ Payment processing lifecycle (authorization, clearing, settlement) β€’ Card types: credit, debit, prepaid β€’ Knowledge of fraud types (card-not-present, skimming, phishing) β€’ Familiarity with PCI compliance and security standards Preferred Qualifications β€’ Bachelor’s degree in Computer Science, Statistics, Finance, or related field β€’ Experience in fintech, banking, or payments β€’ Knowledge of APIs and payment gateways β€’ Exposure to AML/KYC processes