Arijit Guchhait
CONTACT INFORMATION
Tampa, FL **613
adhnwx@r.postjobfree.com
https://www.linkedin.com/in/arijitguchhait/
https://github.com/aguchhait-bit
SUMMARY
Junior Data Analyst with 2 years of professional experience in production line and 2 years of graduate level academic experience in data analysis, machine learning and supply chain management. Experienced in interpreting and analyzing data for data informed decision making to optimize productivity, cost . Increased sales by 15%. A passionate, fast learner and encouraging team member who put the company’s values and mission first. Skills
● Python
● SQL ( Oracle SQL Developer, MySQL, SQL Server)
● Data Analysis, Data Mining, ETL
● Data Visualization (Tableau, SSRS)
● Machine Learning (Jupyter, Scikit-learn, Numpy, Pandas, Seabron, Matplotlib, Keras)
● MS Office ( LOOKUP, Pivot Tables, CountIf, Forecasting, VBA, Hypothesis Testing)
● AutoCAD
● R
● Production control, Material handling, Facility Planning, Time and Motion study, statistical quality control and Six Sigma
WORK EXPERIENCE
Levram Lifesciences Pvt. Ltd
Junior Data Analyst
12/2016 -12/2018
● Conducted time studies and motion economy studies of workers on the production line to find opportunities for improvement
● Designed, plan, and develop programs to optimally extract, transform and load data from data sources to the target sources
● Design, maintain and enhance complex SQL query, stored procedures, ad-hoc analysis
● Design, develop, and maintain SSRS and Tableau dashboards to generate reports on regular basis
● Performed NLP, Machine Learning(Scikit-learn, panda), sentiment analysis to improve marketing strategy
● Used statistical techniques for hypothesis testing to validate data and managerial strategy
● Performed market analysis to efficiently achieve objectives, increasing sales by 15%
● Investigates and conduct studies on the forecasts, time series analysis using Microsoft Excel pivot tables and VLOOKUP Functions
● Reported weekly to the Plant Manager with analysis on KPIs, and Root-cause analysis for ongoing problems throughout the production pipeline Education
University of South Florida, Tampa, FL
Master of Science in Industrial Engineering
GPA: 3.63/4
01/2019 - 8/2020
● Key specialized courses: Engineering Analytics, Probabilistic Systems Analysis, Statistical Design Models, Optimization using Operational Research, Industrial Information Systems, Python for Data Science, Production Control, System and Supply Chain Management
Haldia Institute of Technology, India
Bachelor of Technology in Production Engineering
GPA: 7.56/4
08/2012 - 06/2016
Academic Projects
Music Classification Project: Python, Neural Network, Random Forest, XGBoost January 2020
● Utilized data cleansing technique (Panda, Scikit-Learn) and visualization (Seaborn, Matplotlib) in python for data intelligence and analysis
● Built models using Statistical techniques like Bayesian HMM and Machine Learning classification models like XG Boost, SVM, and Random Forest. Tampa Railway Management System: MS SQL, Tableau
January 2020
● Created E/R Diagrams, Data Flow Diagrams, grouped and created the tables, validated the data, identified lookup tables
● Developed tableau visualizations, build, published customized interactive reports & dashboards using tableau server
Ashrae - Great Energy Predictor (Kaggle Competition): ggplot2, Tableau, SVM, K-Means August 2019
● Designed and implemented supervised algorithms like Logistics Regression, Decision trees, XGBoost, SVM’s, Polynomial Regression and Unsupervised Machine Learning algorithms like clustering. K-means Mixture models. Hierarchical Clustering, Anomaly Detection.
● Created dashboards and visualization using ggplot2 and Tableau TRAINING
● Python Basics for Data Science: Authorized by IBM
● Databases and SQL for Data Science: Authorized by IBM
● Neural Networks and Deep Learning: Authorized by IBM
● NLP with Python for ML:Authorized by LinkedIn Learning
● Business Applications of Hypothesis Testing & Confidence Estimation:By IBM PART-TIME EXPERIENCE
Aramark Dining Services
Student Worker
4/2019-4/2020