Shagufta Nousheen

Analytical and detail-oriented Data Analyst with over 5 years of combined experience in leveraging data to optimize operations, improve AI systems, and enhance customer experiences in banking and retail industries. Proficient in SQL, Python, Tableau, and machine learning workflows, with a strong ability to transform complex data into actionable insights. Recognized for driving innovation in autonomous retail technology and streamlining account operations. Adept at collaborating with cross-functional teams to deliver scalable solutions under tight deadlines.

· Played a key role in scaling machine learning workflows for autonomous checkout systems, improving functionality and accuracy.

· Successfully trained team members on process updates, enhancing team productivity and compliance.

· Recognized as a Top Performer for three consecutive cycles for foreign currency cheque (FCC) collections.

· Identified inefficiencies in account activation processes, leading to a 10% reduction in turnaround time.

• Husband's Name: mohammed Abdul Azam
• Date of Birth: 11/25/93

Amazon Go AI Operations Analysis

· Conducted extensive data analysis to improve AI workflows for autonomous checkout systems, resulting in a 25% enhancement in system performance.

· Delivered insights that directly influenced updates to machine learning models, reducing false receipt errors.

Customer Behavior Dashboard

· Designed a Tableau dashboard to analyze customer traffic and behavior patterns, providing actionable insights for resource allocation and store layout optimization.

NRI Customer Account Insights

· Used SQL to analyze customer account data, streamlining the conversion of savings accounts to NRI accounts, and improving onboarding efficiency.