Abhinav Joshi

Boston, MA ***** 857-***-**** adg377@r.postjobfree.com www.linkedin.com/in/Abhinav-Joshi21 Education:

Northeastern University, Boston, MA

Master of Science in Industrial Engineering (GPA: 3.8) Aug 2020 Relevant coursework: Deterministic Operation Research, Stat Methods in Engineering, Lean Concepts & Application, Supply Chain Engineering, Deep learning, Simulation Analysis Rajiv Gandhi Prodyogiki Vishwavidyalaya, India

Bachelor of Engineering in Mechanical Engineering June 2018 Technical Skills:

Tools/Applications : Advanced Excel, MS Access, MS Word, MS PowerPoint, Visio, Arena Core Competency : Value Stream Mapping, Flow Analysis, Root Cause Analysis, Inventory Management, Demand Forecasting, Labor Management, Python Simulation, MOST Data Analysis Tools : Python, MySQL, Minitab, PowerBI, Tableau Design Software : AutoCAD, Google SketchUp, Solidworks Machine Learning : Regression model, Time Series model, Convolutional Neural Network, Pandas, Tensor Flow, NumPy, Long Short-Term Memory

Work Experience:

Invata Intralogistics, Burlington, MA (Domain: Warehousing Automation) Junior Application Engineer Co-Op May 2019 – Dec 2019

• Implemented predetermined time standards in designing workstation to increase labor efficiency by 28%

• Developed PowerBI dashboards to analyze the daily performance based on various KPI's for client warehouses using inbound and outbound data generated by the warehouse management system

• Designed schematic plan for the warehouse expansion and installation of new equipment in the warehouse according to client`s requirements

• Collaborated with the solution design team and developed costing templates using advanced Excel formulas and Pivot table for various automated storage and retrieval systems

• Created 3D drawing of proposed warehouse plan for better representation, analysis, and understanding of clients

• Created a database containing CapEx And OpEx data of all the previous and current clients Academic Projects:

Pack-Station Simulation Feb 2020 – Dec 2020

• Generated packing times using MOST time standards for 2 different categories of items

• Created python simulation for pack stations to process peak demand of 7756 Orders and 43000 Units

• Optimized simulation process by iterating through factors such as number of SKU presented, number of orders presented, queue length, number of stations

Process Analysis of Dunkin Donut Feb 2019 – Apr 2019

• Created values stream map and process simulation of Dunkin Donut`s coffee making processes using Arena Simulation

• Collected and analyzed data of over 100 customers to find variations in arrival and average process time

• Reduced cycle times of coffee making processes by an average of 20% of the initial cycle time Malignant Mutation Prediction in Metalloproteins Feb 2020 – Dec 2020

• Analyzed and cleaned genome dataset containing 900 sequential points and 76315 spatial points

• Implemented and trained data using XGBoost and FCNN Models, achieved an accuracy of 83% and 93% respectively in predicting malignant mutation at the metal-binding sites of metalloproteins Statistical Analysis of Olympic History Oct 2018 – Dec 2018

• Identified factors which impacted the Olympic event medal outcome based on data history of Olympic

• Analyzed data containing 134732 unique values of participation with a total of 271116 participation using Python, MS Excel, and Minitab

• Forecasted the chances of a country winning a medal in a certain event using conditional probability

Contact this candidate