ตัวอย่าง Resume วิทยาศาสตร์ข้อมูล (Data Science) ฉบับที่ 192

Professional Summary

Highly motivated Sales Associate with extensive customer service and sales experience. Outgoing sales professional with track record of driving increased sales, improving buying experience and elevating company profile with target market.

Highlights

• C++, Python, R, SQL, SSAS, QlikView, MatLab, Python, Hadoop, HIVE, Microsoft Office [Excel, Word, Powerpoint] Honors: MCPS - 70
• - Customer promotional sensitivity and valuation - Walmart (capstone) January 2016. - Evaluated incremental revenue gain from customer initiated discounting options for Walmart. - Recommended promotional strategies and identified target cohorts based on statistical analysis (log regression using interactions, T-Tests in R) of significance and sensitivity of customers who use discounting options - coupons and ad match Classify operating condition of water pumps in Tanzania - University of Texas at Austin November 2015. - Developed a random forest based algorithm to predict faulty water pumps as a part of online challenge to help the Tanzanian Ministry of Water. - Pre-processed data by feature selection, imputation and adding open data; handled class imbalance by upsampling, downsampling, ROC curves and developed classification models in Python - SVM (70%), naïve bayes (65%), logistic regression (69%) and random forest (82% overall accuracy) Understanding correlation between reviews and car sales using sentiment analysis and PageRank - University of Texas at Austin September 2015. - Analyzed sentiments of different car model reviews from Edmunds.com using textblob, NLTK in Python. - Identified preferences between car models using weighted PageRank algorithm to create a product network and found 70% correlation with sales Analyzed economic inequality in the US based on societal characteristics by using k-means in Python - University of Texas at Austin August 2015. - Developed an unsupervised clustering model to identify the economic inequality among people in the US based on the General Social Survey data - Demographic segmentation based on varying societal and demographic characteristics using k means algorithm in Python that could be used for marketing strategies and framing socio-economic government policies.

Experience

Education

• Master of Science: Business Analytics
• The University of Texas at Austin · Business Analytics 3.74 / 4.00 · May 2012
• Bachelor of Technology: Chemical Engineering
• National Institute of Technology - Trichy · Chemical Engineering 8.78 / 10.00
• 461, MCPS - 70-463, Data Science - Duke University (Certificate of Distinction, Coursera); Thorogood Associates; Passion Award (2014), NITT; 2nd in Class, (2012)

Skills