Senior Data Analyst

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 acumen—someone 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 • 3–6 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