1. SAUMITRA SHARMA
Mountain View, CA  510-6405788  saumitra.sharma1@gmail.com  www.linkedin.com/in/saumitrasharma/
MS in Analytics, a Marketing Analyst with work experience in campaign, and product analytics. An
experienced project leader, who takes a practical engineering approach toward problem solving and has
excellent skills in database management (SQL), SAS programming, and Tableau.
E X P E R I E N C E
LatentView Analytics Corporation SF Bay Area, California
Senior Analyst
Client: Paypal: June 2014 – Feb 2015
 Campaign Analytics
o Built statistical models to create target list of customers.
o Engaging with the cross functional team to launch, and measuring the campaign
o Delivering the insights to the upper management in an actionable format
Client: YouTube-Google March 2015 - Present
 Product Subscription and Campaign Analytics
o Build user metrics tracking system for YouTube Originals.
o Design/Launched/Analyzed experiments to measure the impact on user behavior (on views,
watch time, and daily actives)
o Measuring effectiveness of email, promo campaigns for Red Users
o Profiling Red Users to reduce churn
Modelytics India Private Limited Bangalore, India
BUSINESS ANALYST Jan 2012 - May 2013
Client: US based micro finance bank.
 Build scorecards merging internal and TransUnion data, reducing the customer default rate from
25% to below 10%.
 Achieved a response rate of 1.5% during the first round of a direct mailing campaign.
JSW Steel Limited Bellary, India
JUNIOR MANAGER Sep 2010 – Nov 2011
Managed the project of a Water Treatment Plant for Steel Making Shop supervising a team of 15
E D U C A T I O N
Louisiana State University Baton Rouge, LA
MASTEROF SCIENCEIN BUSINESS ANALYTICS (MSA) May 2014
MS Ramaiah Institute of Technology, VTU Bangalore, India
BACHELOROF ENGINEERING IN MECHANICALENGINEERING June 2010
C E R T I F I C A T I O N S
SAS Certified Base Programming for SAS 9  SAS Certified Advanced Programming for SAS 9
Certificate in Investment Banking and Corporate Finance
S K I L L S / A C T I V I T I E S
Statistical Techniques: Regression, Factor Analysis, Customer Segmentation, Survival Analysis, Time
Series Forecasting, Data Mining, Neural Network, Decision Trees.
Business Intelligence: Database / OLAP / OLTP, ETL Processes / Data Warehouse, Multi-
Dimensional Cubes, Tabular Models, Tableau / Visual Analytics
Analysis Software: SAS, Google SQL, Dremel SQL, SQL – MapReduce, Teradata, SQL Server 2012,
SQL Visual Studio 2010, Advanced Excel Solver Package