Data Analyst Supply Chain

SUMMARY

ANJALIGUPTA RAGHAVENDRA

Data Analyst Business Intelligence Analyst Python, SQL, Tableau, AWS

+1-908-***-**** ***********.***********@*****.*** LinkedIn GitHub Data Analyst with 3.5 years of experience in finance, supply chain, and healthcare analytics, specializing in Python, SQL, and Power BI for ETL pipelines, predictive modeling, and interactive dashboards. Proven ability to automate workflows, optimize KPIs, and deliver data-driven insights for cross-functional teams. Expertise in SAP S/4HANA, AWS, and Azure Data Factory for large-scale data integration. Strong background in Agile methodologies, stakeholder communication, and regulatory compliance SKILLS

Programming Language: Python, SQL

Data Visualization: Tableau (Server, Prep, Public, Desktop), Power BI, Alteryx Databases: MySQL, SQL Server, PostgreSQL, Oracle

Statistical & Machine learning Libraries: NumPy, Pandas, Matplotlib, SciPy, Scikit-learn, Seaborn, TensorFlow, DAX Data Reporting and Automation: Microsoft Excel, SQL Server Management Studio (SSMS) Documentation: Functional Requirement Document, Business Requirement Document, SRS, Use Cases, User Stories Supply Chain Analytics: Inventory Optimization, Demand Forecasting, Supplier Performance Analysis, Procurement Analytics, OTIF Tracking Project Management & Tracking Tools: Jira, Microsoft Visio, Joint Application Development, User Acceptance Testing ERP & Cloud Technologies: SAP S/4HANA, AWS (S3, EC2), Azure Data Factory for ETL, DataBricks EDUCATION

Master of Science in Information Science, New Jersey Institute of Technology, Newark, USA Bachelor of Engineering in Information Science, Vidya Vikas Institute of Engineering and Technology, Mysuru, India EXPERIENCE

Wells Fargo, USA Data Analyst – Supply Chain Analytics June 2024 - May 2025

Collaborated with product managers, finance analysts, and logistics teams to gather reporting requirements for dashboards, risk models, and operational KPIs

Integrated financial and inventory data from SAP S/4HANA into AWS S3 and Redshift via Python-based ETL pipelines, ensuring compliance with Wells Fargo’s regulatory and SLA standards

Extracted and transformed large-scale datasets from supplier ledgers, warehouse systems, and freight tracking sources to support supply chain analytics

Designed validation rules to ensure cross-system data consistency across POs, GRNs, delivery schedules, and vendor credit tables

Developed predictive models in Scikit-Learn to forecast revenue and optimize inventory, improving OTIF delivery by 40%

Created Power BI dashboards tracking key metrics such as Net Interest Margin, vendor risk, working capital turnover, and delivery performance

Automated recurring financial and supply chain reporting using SQL and DAX, reducing manual workload by 30% and improving report accuracy

Partnered with audit and compliance teams to ensure models adhered to Basel III guidelines and third-party vendor SLAs Infosys Ltd, India Data Analyst Aug 2022 - Aug 2023

Collaborated on ETL operations across 20 business units, applying advanced Excel functions and Python for data cleaning and transformation; loaded curated datasets into Truist Bank’s analytics database

Directed data validation and defect resolution efforts, achieving 100% compliance with state-specific transformation rules outlined in the mapping documentation

Executed complex SQL queries (CTEs, window functions, joins, indexing) to enforce transformation logic and maintain data integrity; used Python for cross-functional business analysis

Led Escheatment & Tax compliance projects using Kanban methodology, defining clear milestones & deliverables, ensuring timely completion

Leveraged Jira, SharePoint, & Excel tools (PivotTables, VLOOKUP) to monitor & report on project status, improving reporting accuracy by 20%

Conducted A/B testing with statistical models to evaluate digital savings promotions, achieving a 6% increase in conversion rates

Automated file extraction and classification workflows using Python, streamlining child record processing and accelerating financial closing procedures

Designed and deployed 10 interactive Tableau dashboards for real-time KPI tracking, delivering insights into demographic behavior and departmental performance

Sun Pharma Health, India Jr. Data Analyst Jan 2021 - Jun 2022

Developed complex SQL queries on SQL Server and PostgreSQL to extract high-volume healthcare datasets, improving data retrieval speed by 15%

Integrated data from EHRs, insurance claims, and provider systems into a centralized warehouse, enhancing data reliability and consistency

Cleaned and transformed large datasets using Python and SQL, enabling accurate analytics for clinical and financial decision-making

Ensured HIPAA and CMS compliance by validating PHI and sensitive patient data, mitigating regulatory risk

Performed exploratory data analysis and root-cause investigations using Python and Databricks, uncovering trends in readmissions, denials, and provider inefficiencies

Built predictive models to forecast patient readmission risk, improving prediction accuracy by 20% and aiding proactive care planning

Conducted cost-benefit, GAP, and impact analyses to optimize resource utilization and reduce administrative overhead by 15%

Designed and deployed Power BI dashboards to visualize hospital KPIs and claims metrics, enhancing stakeholder decision-making efficiency by 20%

Automated data pipelines, dashboard refresh cycles, and claims reporting workflows using Python and SQL, improving data accuracy and reducing manual workload

ACADEMIC PROJECTS

EchoVerse: Decoding the Sentiments and Success of Song sci-kit-learn, NLTK, TF-IDF, RFC, Spotify & Genius API, Matplotlib Link

Extracted 4000+ songs via Spotify/Genius APIs (95% integrity) and built Modify, a mood-based playlist generator using K-means, NLTK, and topic modeling

Built Vibe Care, a music therapy app using TF-IDF and Random Forest to generate personalized playlists across four emotional vibes Crowd Management System Python, Deep Learning, OpenCV, YOLO & NMS algorithms, Image Processing Link

Designed a real-time crowd-monitoring system using DNN, YOLO, NMS, and GPU-accelerated Python/OpenCV to analyze 200 FPS density data and classify zones, ensuring 100% COVID-19 compliance

Automated safety violation alerts with 93% accuracy, boosting security response time and operational efficiency in high-traffic zones

Contact this candidate