Pruth Parinkumar Dharia

Monmouth Junction, NJ ***52 908-***-**** adnm5d@r.postjobfree.com www.linkedin.com/in/pruth-dharia-271707a4 A passionate Industrial Engineer leveraging experience working with complex data management and supply chain analysis, seeking a challenging role that enables me to utilize my skills in operational analysis and supply chain planning SKILLS

Data Analysis: Statistical learning, Predictive modeling, Simulation, Data mining, Data visualization, KPI management Supply Chain: Demand forecasting, Inventory management, MRP, Logistics planning, Sourcing and Procurement Financial Analysis: Cash flow analysis, Cost estimation models, EOQ models, ROR analysis, Make vs Buy models Manufacturing: Lean manufacturing, Kaizen, Continuous improvement, SPC, SMED, MOST, DMAIC, 5S, FMEA Software Skills: MS Office, Advanced Excel, SAP PP, SQL, Tableau, Python, R, Minitab, Power BI, Simio, AMPL(CPLEX) PROFESSIONAL EXPERIENCE

Monarch Fibre Foils

Supply Chain Engineering Intern (January 2017 – June 2017)

• Performed data cleaning using analytics tools, enabling the team to improve the data driven decisions

• Assisted in New Production Introduction (NPI), from ideation to continuous mass production of L.L.D.P.E. Bags

• Forecasted the material requirements based on the individual material’s lead time and seasonal demand variability

• Developed workflow charts and integrated the machining processes for manufacturing 6 unique type of recyclable fiber drums

• Developed a dashboard using Advanced Excel functions, enabling the team to track the work in process for 20 unique parts as per the changing production needs

EIMCO ELECON, Gujarat, India

Engineering Intern (May 2016 – June 2016)

• Partnered with the demand planning team in identifying KPIs using data visualization tools for the production process, resulting in the reduction of stockouts of vehicle parts from 23% to 8%

• Created a supplier database, formulated a quality plan to efficiently allocate resources

• Used Excel and SQL and to create a Supplier Pool Matrix for 18 suppliers to reduce risks in procurement of parts

• Gained on hand experience on working with SAP PP (Production Planning) module

• Developed workflow models and performed time study and line balance techniques to propose modifications, resulting in a 30% reduction in transportation time

PROJECTS

Data Analytics and Demand Planning

Predicting risk of car insurance claim (October 2018 – December 2018)

• Used R Studio extensively to enhance the raw training dataset by removing invalid data points

• Predicted car insurance claims using machine learning techniques such as SVM, logistics regression and achieved 95% prediction accuracy using LDA, QDA and KNN model fitting methods using Python and R studio Optimal class scheduling at Texas A&M University (March 2018 – May 2018)

• Developed and presented an optimal departmental class schedule using CPLEX (AMPL) linear programming tool, meeting all time and infrastructural constraints, maximizing the professor’s course and timeslot preference ratings Demand forecasting for Arconic Industry (September 2018 – December 2018)

• Devised (short-term) biweekly and (long-term) 6 months forecast leveraging MS Excel, R studio & Minitab

• Studied the demand trends and developed SQL queries to efficiently manage data using MySQL for 520 unique parts Supply Chain Analysis and Process Control

Supply chain planning for VTI Industry (September 2018 – December 2018)

• Developed replenishment strategies and created an Excel tool for calculating optimal reorder point, reorder quantity and safety stock requirements

• Built a linear program using Excel VBA, assisting in maximizing truckload and reduced transportation costs Analysis of Chicago car towing data (February 2020 – May 2020)

• Designed a dashboard using Tableau, displaying data of the towing pattern based on the car model/company

• Anticipated the reasons for incorrect VIN of 17,304 cars using terrestrial coordinates and tree charts in Tableau Statistical process control of a manufacturing process (September 2019 – December 2019)

• Modelled an anomaly detection algorithm for 550 data points with 209 variables and established process limits to develop control charts for detecting non-conforming parts (out of control data) for future analysis EDUCATION

Texas A&M University, College Station, Texas, USA May 2020 Master of Science - Industrial and Systems Engineering (specializing in data analytics) G.H. Patel College of Engineering & Technology, Gujarat, India June 2017 Bachelor of Engineering - Mechanical Engineering