Job Summary:
About the Role
Customer is expanding its analytics capability to support the growing ecosystem of device resale, trade-ins, and refurbishment programs across banking institutions, large reseller networks, and channel partners.
We are looking for a high-performing Data Analyst who can turn multi-source data into actionable insights that improve pricing intelligence, risk assessment, partner performance, and operational efficiency.
This role is ideal for someone who combines strong analytical and technical skills with solid business acumensomeone who understands how device resale markets work, how banks and sellers process trade-ins, and how pricing, quality, and fraud indicators impact downstream decisions.
Key Responsibilities
Analyze large volumes of trade-in, resale, and device lifecycle data from banks, marketplaces, and reseller partners
Build analytical models and dashboards that improve pricing accuracy, forecast resale value, and identify market trends
Evaluate seller and banking partner performance, identifying patterns of anomalies, quality issues, or potential fraud
Perform deep-dive analysis on device condition, grading variations, recovery values, and channel profitability
Create efficient SQL queries and Python scripts for data extraction, cleansing, and transformation
Collaborate closely with product, business, risk, and operations teams to translate insights into decision frameworks
Develop Tableau dashboards for senior leadership, focusing on KPIs such as resale uplift, trade-in volume, partner trends, and customer behavior
Support A/B experiments and initiative performance measurement
Ensure data consistency, quality, and governance across multiple internal and external data sources
Present analytical findings clearly and concisely, with a strong narrative and actionable recommendations
Required Skills & Experience
36 years of experience as a Data Analyst, Business Analyst, or similar role
Strong SQL expertise for data querying, joining large datasets, and optimizing pipelines
Hands-on experience with Python (Pandas, NumPy, data cleaning, EDA, scripting)
Working knowledge of Tableau for dashboard creation and storytelling
Experience analyzing multi-source datasets such as financial institutions, seller networks, marketplaces, or trade-in systems
Strong understanding of device resale or trade-in workflows (e.g., grading, pricing, lifecycle, channel economics) preferred
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