Two_Column_Resume_Siddharth
Author:
Siddharth Jain
Last Updated:
há 9 anos
License:
Creative Commons CC BY 4.0
Abstract:
Siddharth Jain's CV
\begin
Discover why over 20 million people worldwide trust Overleaf with their work.
Siddharth Jain's CV
\begin
Discover why over 20 million people worldwide trust Overleaf with their work.
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\namesection{Siddharth}{Jain}{ \urlstyle{same}
\href{mailto:sjain65@uic.edu}{sjain65@uic.edu} | 312.774.0496
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\section{Summary}
\textbullet{} Have 5+ years of experience with .NET \\ and Microsoft BI- T-SQL, SSIS \& SSRS.\\ \\ \textbullet{} Gained good understanding of Python, Rapidminer \& R as part of coursework.\\ \\
\textbullet{} Worked in process consulting space for about a year.\\ \\
\textbullet{} Had a brief stint as professional \\ derivatives trader \\ \\
\textbullet{} Familiar with Tableau \& Jasper \\ Reports Server.
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\section{Education}
\subsection{University of Illinois at Chicago}
\descript{MS in Business Analytics}
\location{Expected May 2016 \\ Cum. GPA: 4.00}
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\subsection{Great Lakes Institute of Management}
\location{PGPBABI \\May 2014 to July 2015}
\location{ Cum. GPA: N/A}
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\subsection{Devi Ahilya Vishwavidyalaya}
\location{B Eng. in Computer Science \\Aug 2006 to May 2010}
\location{ Cum. GPA: 3.6}
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\section{Coursework}
Data Mining \\
Text Mining \\
IBM Watson Analytics\\
Game Theory\\
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\section{Skills}
\subsection{Programming / Web}
C\# \textbullet{} ASP.NET
\subsection{Data Analytics}
Rapid Miner \textbullet{} Python \textbullet{} R
\subsection{Reporting}
Tableau \textbullet{} Jasper Reports Server \textbullet{} SSRS
\subsection{Database}
SQL Server \textbullet{} SSIS
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\section{Experience}
\runsubsection{Sumtotal Systems}
\descript{| Software Design Engineer 2 }
\location{May 2014 – Jul 2015| Hyderabad, India}
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\item Worked in R\&D engineering team to create next generation reporting platform for Learning and Talent management products.
\item Was involved in complete product lifecycle - Design, Development, Release and Bug Fixing.
\item Created a localization monitoring tool which can sniff through industry standard XML based TMX and Jaspersoft Schema files and fix potential issues. This optimized localization process reducing the turnaround time by 60\% and bug count by over 80\%.
\item Created a live link functionality – Audience will be notified for scheduled reports though a hyperlink via email, clicking on which data will be populated as per the roles and permissions assigned to the user in real time. To materialize this I applied concepts of SSIS, Sql CLR stored procs, RESTful API.
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\runsubsection{Futures First}
\descript{| Market Analyst Trainee}
\location{May 2013 – Jan 2014 | Hyderabad India}
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\item Traded out-rights and calendar spreads of futures contracts of Arabica and Robusta Coffee at ICE \& LIFFE Exchanges.
\item Managed a portfolio in access of \$150,000.
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\runsubsection{Infosys Limited}
\descript{| Systems Engineer}
\location{June 2010 – April 2013 | Hyderabad India}
\begin{tightemize}
\item Developed UI using ASP.NET for the payroll application for the client (Microsoft).
\item Automated the data creation procedures using concepts of dynamic SQL. This helped in reduction in development time by 70\%.
\item Was involved in process consulting for the internal procurement application - MS Expense. Duties involved managing Support teams across Poland and India, coordinating UAT and managing ad-hoc reporting requests.
\item Created SSIS packages and SSRS reports for the purpose of scheduled and ad-hoc reporting for expense tracking application - MS Expense (Microsoft).
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\section{Academic Projects}
\runsubsection{Picture Perfect}
Implemented IBM Watson cognitive platform over an android app providing just in time answers to DSLR camera users. The DSLR has multitude of settings which are difficult to harness owing to highly technical documentations. The app tries to overcome the barrier by providing crisp answers in colloquial style. I was involved in training the engine and optimizing the Q\&A performance.
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\runsubsection{Recruit Ponpare}
This Japanese coupon site held a coupon purchase prediction competition at Kaggle.com. We adopted a unique approach to boost performance of our statistical model – Once we translated the Japanese text, we pulled the census data to figure out prefectures with higher levels of median income. This validated the relatively high concentration of coupons being sent to these localities in both training and test data sets. I was involved in building the translator app using Bing Translator web service and in building the model. Skills Used – Python, C\# \& Tableau.
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