Data Analyst Python

Aman Kumar

********@***.*** jwww.linkedin.com/in/aman-kumar-analytics jH+1-858-***-****

**** * ***** *** ***** Dr, Tempe, AZ 85281

EDUCATION

W. P. Carey School of Business, Tempe, AZ

Master of Science, Business Analytics Aug. 2018 – May. 2019 GPA: 4 / 4

SRM University, Chennai, India

Bachelors of Technology, Mechanical Engineering Aug. 2012 – Jun. 2016 GPA: 3.4 / 4

SKILLS

Data Analysis: Data Mining, Data Visualization, Database Management, Data Modeling and Optimization, Statistical Analysis, A/B Testing, Natural Language Processing, Business Intelligence, Big Data Statistical Analysis Tools: R, Python, SAS, IBM SPSS, MATLAB, Google Analytics Data Visualization Tools: Tableau, PowerBI, Qlik View, Qlik Sense Business Intelligence Tools: PowerBI, Tableau, MS PowerBI, Oracle BI DBMS & Warehousing Tools: MS SQL Server, AWS, MongoDB, Azure Programming Languages: Python, R, SAS, SQL, JAVA, JSON, C#, Typescript Optimization Tools: Excel Solver, @Risk, Precision Tree, Google Sheets, Arena Software Development Life Cycle: Agile, Waterfall, Scrum, Lean Six Sigma MS Office: Excel (Pivot Tables, power queries, Macros), Power Point, Access, Word Collaborating Tools: Asana, SharePoint, Confluence, GIT, SVN, Slack, Front Operating Systems: Windows, MacOS

WORK EXPERIENCE

Utility Smart, Phoenix, Arizona

Data Analyst Aug. 2019 – Present.

Working closely with Utility Smart executives and the software development team to bring data analysis support to the company’s services

Contributing to Utility Smart’s ‘Smart Assistant’ to create business performance and resident billing dashboards for the management, customers, and the residents using smart devices by processing intents and metrics using Amazon Lex, and Google Dialogflow

Designed and created Utility Smart’s Invoice Validation Tool using analysis of utility provider rate structures to recalculate invoices in real time to maintain data integrity by catching provider and Utility Smart errors. Tool is a custom web app interface made for team members to use the solution created using Excel, SQL Server, and Python

Developed a prediction tool for budgeting Utility expenses on new upcoming properties for multifamily management companies employing several predictive modeling techniques in python

Created an Utility Budgeting and Accrual Tool for Utility Smart’s multifamily property management clients by implementing forecasting techniques using both historical and benchmarked data sets Arizona State University, Tempe, Arizona

Research Specialist (Arizona Lottery) Jul. 2019 – Aug. 2019

Optimized Arizona Lottery’s Paid Media Mix by identifying campaigns with the highest revenue impact

Developed a feasibility proposition for the launch of a high-value tickets

Designed an optimal product mix for the ’Fast Play’ line of products

Analyzed the demographic composition of the Players Club base for more targeted offers FetchRev, Tempe, Arizona

Data Scientist Intern Apr. 2019 – Jun. 2019

Worked on Attribution modeling framework for FetchRev (marketing startup) to find optimal promotional strategies. Applying Natural Language Processing to perform customer segmentation to make the promotions more targeted according to user preferences hence reducing waste

Analyzed the coupon text used for the promotions in python, to create clusters (using K-means and silhouette Analysis) of similar businesses by finding the cosine similarities between the promotions

Used the business clusters to categorize the subscribers according to their interests by using the coupon redemption data

Analyzed the coupons using Latent Dirichlet Allocation to find the most effective words that drives the interest of customers in each business cluster

Analyzed the coupon effectiveness by analyzing the conversion funnel and working on creating a multivariate test for successful promotions

HonorHealth, Phoenix, Arizona

Data Analyst (Capstone Project) Nov. 2018 – Apr. 2019

Optimized Inventory and existing transport pipelines in Honor health facilities to reduce the on-demand delivery costs and logistics costs by 20% (of $1.6 million), also created new transport pipelines by analyzing previous years data to find trends in demands across different departments and routes using Tableau and python

Used python to do data cleaning for addresses and other string discrepancies for better analysis

Created visualizations using tableau to identify consistent trends in demands and focus areas for cost reduction

Applied Pareto’s 80/20 rule to identify most costly routes and primary cost reduction areas

Used Google Cloud Platform’s geolocation API to find the coordinates of the locations to build a pathoptimizing model which could potentially reduce costs by an additional 15% Infosys Limited, Bengaluru, India

Systems Engineer Jun. 2016 – Jul. 2018

Assisted clients in addressing complex business problems in the agricultural industry through application of relevant technology and helped increase the revenue by $500,000

Reduced transaction time per customer from 70 seconds (manual transaction) to 12 seconds (digital transaction) increasing the operation speeds by 83% helping in increase of business capabilities

Reduced the warehouse operations cost by 10% through analyzing the inventory data for warehouse space optimization using SQL for generating reports based on seasonal production using Tableau

Developed Android (Java), and web platform (TypeScript) for monitoring, and analyzing crop health, which helped in crop protection and reduced crop mortality rate by 15%

Developed a hotel reservation and checkout application using python and created its database using MySQL PROJECTS

Taxi Trip Duration Prediction

Built a model for New York Taxi to predict the duration of travel using 1.4 million historical records

Performed Visual Data Exploration, outlier detection and treatment, and feature engineering to increase the predictive efficiency of the model

Stock market prediction through sentiment Analysis – Time Series Forecasting

Performed Sentiment Analysis on 10 years of New York Times Articles to predict the Dow Jones index and the effect of the news sentiment on Stock Market

Used day wise closing value of Dow Jones for past 10 years combined with the sentiment score of each article generated using “SentimentAnalysis” library in R

Compared the predictions with the traditional forecasting techniques like Holt-Winter forecasting models and observed that sentiment analysis reduced the RMSE by 30% LEADERSHIP POSITIONS

Project Lead, Utility Smart Oct. 2019 – Present.

Project Lead for the development of three Utility Smart products and services: CompassAI [revamp], Provider Invoice Validation Tool, and Utility Budgeting and Accrual Tool Director of Communications, MSBA Leadership Board Aug. 2018 – May. 2019

Build a sense of community among the MSBA students from all around the world so they gain an appreciation for their differences and discover what they have in common Chapter Head, Youth United Chennai Chapter, India Jun. 2014 – Jun. 2016

Responsible for the overall functioning of the chapter including financial, operational responsibilities and event planning

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