Data Analyst(Python,R,Tableau,SQL,Mapreduce, Stat Modeling)

Prerna Singla

*** ***** ***** ****, ********* (CA) - 94086

Phone – 001 408-***-****, **************@*****.***

Summary

An experienced data enthusiast with analytical and business intelligence skills bundled with strong business acumen. Well equipped to leverage my expertise to understand real problems and to come up with logical business driven solutions.

Education

Database and Data Analytics, September 2015 (expected)

UCSC Silicon Valley Extension, Santa Clara

Master of Business Administration, April 2011

School of Petroleum Management, PDPU, India

Bachelor of Science, April 2009

Kurukshetra University, India

Core Specialities

Software Skills: SQL, Python, R, Hadoop (Mapreduce), MongoDB, MS Office (Excel, Power Point)

Platforms: Windows, Unix, AWS ec2

BI Tools: Tableau and its integration with R, Cloudera Live and Google Analytics

Analytical Skills - Data Mining and Analysis - Statistical Forecasting

- Machine Learning - Excel modeling

- SQL Queries and Reports - Dashboard & Data Visualization

Coursework

-Business Intelligence & Data Mining - Data Analysis & Visualization

-Relational Database Design and SQL Programming - Project Management

-Python Programming - Big Data: Tools & Use Cases

-Hadoop: Distributed Processing of Big Data - Business Research Methods

Professional Experience

Data Analyst Intern, Relishly, Mountain View April 2015 – Present

Skills Required: Python, Machine Learning, AWS, MongoDB

Optimizing the search relevance for recommender system in accordance with the user behavior and NLP

Log Analysis and generating different insights to understand users search criteria’s to make the product search experience better

Collecting data, text standardization and performing text mining using different python libraries to create clusters and classify to compare the results and improve search of the platform

Developing modules in python and performing CRUD operations in MongoDB

Analyst, Infraline Energy, New Delhi April 2011 - July 2013

(Awarded ‘Special Performance Award’ for executing excellence in research assignments)

Skills Required: Data Analysis, Data Visualization, Modeling, Market Research

Integral part of team throughout data gathering, data analysis framework involving data cleaning, processing, analysis, and visualization

Conducted a range of statistical analyses to provide valuable data-driven insights for business decision making

Prepared several analytical reports comprised of different data modeling techniques such as time series analysis, financial modeling, and trend mapping

Built visual analytics using business intelligence tool(Tableau) for project deliverables to derive actionable intelligence from end results

Managed research-on-demand and data support for domestic and international clients

Conceptualized analytical papers on latest industry developments assessing market potential and economic viability

Analyst Intern, Infraline Energy, New Delhi April 2010 - June 2010

Skills Required: Data Analysis, Excel Modeling, Data Visualization

Carried out an independent statistical modeling forecasting project involving preliminary research, data gathering, complete data processing, data cleaning, visualization and modeling

Academic Projects

Data Warehouse Design with ERD Diagram – SQL

oDeveloped database schema to show relationships of various tables in the database as per client specifications.

oImplemented data warehouse solution in SQL and queries to generate custom reports.

Walmart Recruiting - Store Sales Forecasting

oObjective was to forecast weekly sales for each department in 45 Walmart stores located in different regions and also to carry out statistical testing and validation of the models

oThis project features a time series problem and my predictive model was primarily based on linear regression, Ridge, Lasso Regression and ARIMA time series modeling

Predicting Valued Repeat Buyers Using Purchase History – Kaggle Challenge

oAnalyzed approximately 350 million transactions for 3,00,000 shoppers and 160,000 offers provided to customers for features generations

oImplemented four different machine learning algorithms - Ridge Regression, Logistic Regression, Ensemble Methods and SVM and improved the performance of baseline algorithm by 13%

NYC Subway Ridership Challenge

oTo predict subway ridership in New York City given many different possible factors such as weather conditions, times of the day/month and locations.

oPerformed data wrangling, data exploration, OLS linear regression, statistical testing and data visualization to build a better predictive model

August 2015

Contact this candidate