Data Analyst

Ashish Piya

Atlanta, Georgia 817-***-**** ***********@*****.***

linkedin.com/in/ashishpiya github.com/aashishpiya EDUCATION

The University of Texas at Dallas August 2019

M.Sc., Business Analytics 3.64

Awarded Dean’s Excellence Scholarship for academic excellence Awarded Scholar With Recognition honors

Kathmandu University December 2015

Bachelor of Business Administration, Finance 3.31

Core Competencies: Python, R, Advanced Business Analytics, Data Mining, Data Preprocessing, Data Visualization and Reporting, Data Analytics, Business Intelligence, Big Data Analytics, Statistics and Quantitative Analysis, Predictive Analytics and Modelling, Prescriptive Analytics and Modelling, Machine Learning Algorithm, Classification Algorithms, Regression Algorithms, Feature Selection and Engineering, Data Query, Survival Analysis, Time Series Analysis, LifeTime Value, Segmentation and Clustering, Sentiment Analysis, Exploratory analysis Soft Skills: Agile Project Management Methodologies, Team Work, Data Storytelling, Effective Communication Analytical Tools and Techniques: Python, R, SQL, Advanced Excel, AWS EMR, AWS EC2, Spark (PySpark), Hive, SAS, Stata, Tableau, MapReduce, Ms Project, Jupyter notebook, Torch, Tensorflow, Random Forest, PCA, RNN, Regression, Naïve Bayes, Survival Analysis, Time Series Analysis

Databases: MySQL Server, Oracle

WORK EXPERIENCE

Data Science Consultant

Techfield LLC, Atlanta, GA, USA (contract position) Oct 2019-Present

● Used various web scraping techniques such as Beautiful-Soup, Selenium, web scraping to collect more than 100k house data for a PIMA county

● Used data visualization tools to create meaningful graphs for client team

● Cleaned the data and engineered features for house price prediction model

● Used Machine Learning model to create a house price prediction model for real estate price in Pima County

● Able to achieve a median relative error of 6.8%

● Use statistical and machine learning algorithms involving Multivariate Regression, Linear Regression, Logistic Regression, Principal Component Analysis (PCA), Random Forest, Design of Experiment, Exploratory Data Analysis Data Science Intern

Enterprise Medical Intelligence LLC, Dallas, TX, USA May 2019-Sept 2019

● Conducted exploratory analysis to interpret trends or patterns in complex data sets

● Used data visualization tools to create meaningful graphs for management team

● Worked with Data Science team to create deep learning models for image classification classification model

● Worked within a scaled agile framework setting as a Scrum Master in-training

● Tools & Tech used: Jupyter Notebook (python), Tableau, Agile Project Management, SDLCs, TensorFlow, Keras, CNN Data Analyst

Aayush Trading International, Kathmandu, Nepal July 2015-May 2017

● Performed market and competitor price analysis

● Calculated financial performance indicators to support decision making

● Calculated Customer Lifetime Value to identify key customer segments

● Studied target market segmentation and devised strategic marketing techniques for different cluster of customers promotions accordingly

● Identified product seasonality trend and forecasted demand based on historical sales data ACADEMIC PROJECT

Big Data Project

● Examined consumer complaint database along with zip code dataset and IRS dataset using Hadoop framework

● Used AWS EMR and S3 for the purpose of cloud storage and cluster computing

● Used Hive and PySpark to conduct descriptive analysis leading to meaningful insights

● Identified the group of companies having highest complaints

● Concluded that most of the complaints is against credit score bureaus followed my loan providing institutions

● Tools & Tech used: Linux, Jupyter Notebook, Python, AWS – Elastic Map Reduce, Hadoop, HDFS, Spark (PySpark), Hive, HBase, Sqoop, Flume

Predictive Analytics Project

● Inspected and cleaned marketing catalog data

● Used SAS to perform exploratory analysis and make predictive model

● Developed and tested hypotheses using logistic regression to provide marketing insights

● Created marketing business implication of the analysis

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