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Supply Chain Analyst Intern

Location:
Dallas, TX
Posted:
May 07, 2019

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Resume:

VENKATA SUBRAHMANYA PARUPUDI

Dallas, TX 214-***-**** ac9bno@r.postjobfree.com www.linkedin.com/in/sandeep-parupudi EDUCATION

MS, Supply Chain Management, The University of Texas at Dallas, 2019 BE, Mechanical Engineering, Gitam University, 2016 CERTIFICATIONS AND TECHNICAL SKILLS

Certifications: CPIM (In Progress), CTL, Six Sigma Green Belt, Contracting, Sourcing and Negotiation, TL-9000, Tableau Desktop Specialist, Microsoft Excel Expert, Google Analytics, MSBI, MS SQL Server Reporting Tools: MS Excel (VBS, Macros and Pivot Tables), Power BI, Tableau, Alteryx, SAP Lumira, SAS Software: MS Dynamics NAV, SAP ERP 6.0 (MM, SD, PP), SAP APO 6.0, Visio, Project, MS Access, SQL PROFESSIONAL EXPERIENCE

Southern Enterprises LLC, Supply Chain Analyst Intern Sept 2018 – May 2019

• Conducted Customer percentage analysis in Power BI to identify 75% of customers that contributed to 60% overall revenue.

• Forecasted the product lines for warehouses using ARIMA in R, to aid visibility in planning, labor & equipment management

• Forecasted demand of 3000 items using FGS E-Step; avoided stock-out and avoided approximately $7,000+ sales loss.

• Designed Excel Macro and dashboard to automate the TO Ship & receive process and reduced 5 hrs. manual work per day.

• Built a new items dashboard to increase visibility for sales team and recorded $55.6M sales revenue for the year 2018.

• Followed up on international shipment deliveries from Asia and UK and reduced the shipping delay from 5% to 2%.

• Prepared Power BI report using DAX for On hand, On water& on order shipments’ KPI’s that lead to better decision making.

• Managed SO issues and planned shipments via Dynamics NAV ERP system to ensure 99.9% on-time delivery.

• Generated Vendor shipping performance report, increased inventory turns by 2.5 and reduced excess inventory by 20%.

• Performed ABC analysis on inventory to prioritize investment for 20% of items that make 70% of annual consumption.

• Conducted root causes analysis and collected data for inventory error & exception handling in Database Management System for two distribution centers & presented solutions to senior management with an estimated savings of $100K. VIZAG STEEL, Supply Chain Intern May 2015 – Dec 2016

• Recommended changes in logistics by implementing cross-docking, which reduced transportation cost by 30%.

• Implemented Value Stream Mapping to determine bottlenecks, reduced zero time and increased production rate by 8%.

• Assisted in generating MRP’s in accordance to BOM’s and MPS requirements using enterprise resource planning software.

• Managed overall stock level in lieu of demand to reduce finished goods inventory by 19% and total inventory value by 12%.

• Acted as liaison between internal clients and suppliers to maintain a service level goal of 90% across the organization.

• Developed supplier scorecards to evaluate current suppliers using KPI and resulted in cost savings of $1.1M.

• Performed root cause analysis to eliminate wastes, added value, and significantly enhanced customer fill rate by 70%.

• Exercised inventory control on production floors to minimize $1.7 million of unfavorable material usage variance.

• Analyzed Customs’ data and commodity price trend by Excel to develop bid strategies to help save $5,000 for 30+ bids.

• Monitored demands and supply flow of over 20 SKUs to minimize backorders and maximized fill rates up to 97%. ACADEMIC PROJECTS

Capstone Project STERIS UT Dallas

• Built a custom template in MS Project mapping the over allocation of resources, thereby improving efficiency by 25%.

• Utilized advance excel formulae, INDEX, IF, COUNTIF to build an operations dashboard and increased visibility by 70%. Probabilistic Demand Load Forecasting Base SAS UT Dallas

• Used ARIMA & time series forecasting models in Base SAS to forecast daily & yearly customer loads for retail store data.

• Conducted data cleansing & manipulation on raw temperature & load data using Excel, SAS Enterprise Guide and R. Data Analysis on AirBnB BA with SAS UT Dallas

• Performed predictive analysis using Regression, Clustering, Neural networks, decision trees on AIRBnB dataset in SAS.

• Identified the key factors that affect the room prices among listings across various cities in the United States. Titanic Data Analysis Tableau UT Dallas

• Performed data retrieval, data pre-processing and decision trees.

• Executed K-Mean clustering using Tableau-R integration by invoking Reserve . LEADERSHIP AND AFFILIATIONS

• Supply Chain Leadership Council, Head of Events and Logistics, UT Dallas, 2017- present

• SAP Users’ Group, Member, UT Dallas, 2018 – present



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