Pradeep Sitaula

An aspiring data scientist pursuing an MS in Data Science, bringing an interdisciplinary perspective rooted in Environmental Science and Sociology. Eager to tackle complex challenges, Passionate about leveraging data analysis to derive meaningful insights. Proficient in R programming, Python, Power BI, Tableau, SAS, and Microsoft Excel/PowerPoint, equipped to contribute effectively to data-driven projects. A detail-focused Data Analyst, with expertise including data warehousing, process validation, and business needs analysis. Proven in understanding customer requirements and translating them into actionable project plans, Dedicated and hard-working with a passion for Big Data.

• Member of Institute of Mathematical Statistics
• Lifetime Member of Lions Club- International
• Member of NQPCN (Network for Quality, Productivity and Competitiveness-Nepal)
• Member of NES (Nepal Environment Society)
• Executive Member of FEMSD (Forum of Environmental Management and Sustainable Development, Nepal)

• Introduction to Career Skills in Data Analytics, Feb 2024
• Tableau Essential Training, Nov, 2023
• Data-Driven Decisions with Power BI, May, 2023
• Probability Theory: Foundation for Data Science, October, 2022
• Essential Linear Algebra for Data Science, September, 2022
• Introduction to Ecological Modelling in R Online, July, 2022
• Stats from Scratch and Wiz of Data Viz (Data Science for Ecologists and Environmental Scientists) online, June, 2022
• R Programming, June, 2022
• Data Science: R Basics, May, 2022
• The Fundamental of Digital Marketing, 20/04/2020
• Training on Environmental Impact Assessment, 22nd October to 3rd November 2018
• Training on Nepal GAP Lead Auditor/Assessor, 9th to 12th Feb 2018
• Self-Learning e-course on Material Flow Cost Accounting (ISO 14051), 01st July 2017 to 31st Dec 2017
• Self-Learning e-course on Food Safety Management (Advanced), 15th to 22nd Dec 2017
• Self-Learning e-course on Food Safety Management (Basic), 9th June 2017 to 9th Nov 2017
• E-learning course on Good Agricultural Practices (GAP) for Greater market Access, 4th Nov 2015 to 6th Nov 2015
• Participation in International Training Program on Management Systems under ITEC Scholarship Scheme 2015-16, 31st Aug 2015 to 25th Sept 2015
• Self-learning e-course on Good Agricultural Practices (GAP) for increasing Farm Productivity, Self-Sustainable Production and Market Access, 1 December 2014 to 30 April 2015
• Training of Trainers on Energy Audit, 20th April to 23rd April 2015
• Energy Management System Lead Auditor Training Course, Nov 17 to Nov 21, 2014
• National Workshop on Product Certification, 3rd Nov to 5th Nov 2014
• Diploma in Total Quality Management, Jan 2013 to Dec 2013
• Self-learning e-Course on Green Productivity and Integrated Management Systems (ISO 9001, ISO 14001, OHSAS 18001), 8 May to 7 September 2013
• Quality Management System Lead Auditor Training Course, March 05, 2013 to March 09, 2013
• Environmental Management System Lead Auditor Training Course, June 17, 2012 to June 21, 2012
• Training on Cleaner Production, Joint venture of Ministry of Industry and Commerce and ICS
• Advanced training on "Environmental Impact Assessment", 2007
• Training course on "Remote Sensing (RS)", Dec. 11-19, 2007
• Training on "Geographic Information System (GIS) For the Beginner", 2007
• Computer Operator, April 28 to July 28,2002
• Perfect office handling package in computer, 2058-05-17 to 2058-08-16 ( 2nd Sept 2001 to 1st Dec 2001)

• Causal Inferences: Conducted causal inferences to explore the relationship between grain yield, seeding rate, and historical grain yields. This project serves as the final assignment for the statistical programming course.
• SAS Project for INFS 762 (Data Warehousing/ Mining) Course: Developed SAS code for comprehensive analysis, utilized histograms for effective data visualization and conducted variable selection and fitted logistic, neural network, and SVM/SGD models using Weka.
• Monte Carlo Simulation Study on Upper Confidence Bounds: Conducted a Monte Carlo simulation study to compare three upper confidence bounds for estimating random match probability in a biometric identification system.
• Development of logistic regression models: Developed a logistic regression model for predicting species classification in an unclassified dataset of Microtus skull measurements.
• The Passcodes Project for Modern Applied Statistics I: Conducted an exploratory analysis, performed a formal statistical analysis of the dataset, conducted post-hoc analysis, testing assumptions of models and generated prediction intervals.
• Passcodes Project for Modern Applied Statistics II: Created a covariate, build three regression models for total UD, total DD, and total H times and utilized FDRs to evaluate the normality assumptions of residuals after fitting models for all subjects.