William Senfuma -- Résumé
Auteur:
William Senfuma
Last Updated:
il y a 9 ans
License:
Creative Commons CC BY 4.0
Résumé:
William Senfuma's Résumé
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William Senfuma's Résumé
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\begin{document}
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% NAME AND CONTACT INFORMATION
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\title{William Senfuma -- Résumé} % Print the main header
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\parbox{0.5\textwidth}{ % First block
\begin{tabbing} % Enables tabbing
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{\bf Address} \> P.O. Box 7062,\\ % Address line 1
\> Kampala, Uganda \\ % Address line 2
%{\bf Date of Birth} \> 7$^{th}$ March 1985 \\ % Date of birth
{\bf Nationality} \> Ugandan % Nationality
\end{tabbing}}
\hfill % Horizontal space between the two blocks
\parbox{0.5\textwidth}{ % Second block
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{\bf Mobile Phone} \> +256 777 777 500 \\ % Mobile phone
{\bf Home Phone} \> +256 711 187 737 \\ % Home phone
{\bf Email} \> \href{mailto:wsenfuma@gmail.com}{wsenfuma@gmail.com} \\ % Email address
\end{tabbing}}
%----------------------------------------------------------------------------------------
% PERSONAL PROFILE
%----------------------------------------------------------------------------------------
\section{Personal Profile}
I am a God fearing, enthusiastic and self-motivated team player with at most attention to detail, accuracy and commitment to high quality. My career objective is to meet new challenges and knowledge with a positive attitude in order to achieve the expected organizational productivity and efficiency.
%----------------------------------------------------------------------------------------
% EDUCATION SECTION
%----------------------------------------------------------------------------------------
\section{Education}
%------------------------------------------------
\tabbedblock{
\bf{2010-2012} \> Master of Science (Computer Science)\\
(Machine Learning, Computer Vision, Image
Processing and Pattern Recognition) \href{http://mak.ac.ug}{Makerere University, Uganda} \\[5pt]
\> CGPA: 4.45/5\\
\>\+
\textit{Dissertation Title `Meta Learning for Selection of Best Causal Discovery Algorithms'}
}
%------------------------------------------------
\tabbedblock{
\bf{2005-2008} \> Bachelor of Science (Computer Science, Mathematics) \href{http://mak.ac.ug}{Makerere University, Uganda} \\[5pt]
\>First Class Honours CGPA: 4.55/5\\
\>\+
%\textit{Final Year Project - 89\% }
}
%------------------------------------------------
\tabbedblock{
\bf{1999-2004} \> Advanced Secondary Education - \href{http://spensa.sc.ug/}{St. Peter's, Uganda}\\[5pt]
\>\+
\textit{(Physics, Chemistry, Mathematics) } \> \\
}
%------------------------------------------------
\textbf{Certificates}
\tabbedblock{
\bf{2015-2016} \> Machine Learning | Stanford Online \\
\href{https://www.coursera.org/account/accomplishments/verify/AMLTHMSCUDMS}{Stanford University, Coursera} \\[5pt]
\>\+
}
\tabbedblock{
\bf{2015-2016} \> Big Data Hadoop Foundations | IBM \\
\href{https://www.youracclaim.com/badges/8b5a0955-c713-4944-b2cb-98c3937a7f59/linked_in_profile}{BigData University, IBM} \\[5pt]
\>\+
}
\tabbedblock{
\bf{2008-2009} \> Software Engineering \\[5pt]
\>\+
\textit{National Software Incubation Center (NSIC), Uganda } \> \\
}
\tabbedblock{
\bf{2012} \> Project Monitoring and Evaluation \\[5pt]
\>\+
\textit{Makerere University College of Humanities and Social Sciences, Uganda } \> \\[5pt]
}
\newpage
%----------------------------------------------------------------------------------------
% IT/COMPUTING SKILLS SECTION
%----------------------------------------------------------------------------------------
\section{Key Competencies and Skills}
\skillgroup{Data Science}
{
\textit{Hands-on knowledge in Python scripting and core data science libraries (Pandas, Scipy, Scikit Learn/ sk-learn, Matplotlib and Seaborn), Unix scripting (Shell and Awk) for advanced huge data crunching }\\
\textit{Proficient in Machine Learning, Artificial intelligence, Data Mining, Data Warehousing and Data Modeling}\\
\textit{Practical knowledge in applying machine learning techniques to real life datasets}\\
\textit{Knowledge of Data Visualization tools like QlickView, QlickSense, D3, Matplotlib, Seaborn and Tabluea}\\
\textit{Working knowledge in Big Data technologies - Hadoop, Hive, Pig and Flume}\\
\textit{Proficient in Microsoft Business Intelligence Suite (SSRS, SSAS and SSIS)}\\
\textit{Proficient with Microsoft SQL Server 2008/2012} - database architecture and administration\\
\textit{ETL development using SSIS and Talend Open Studio}\\
\textit{Clustering for market micro-segmentation and Market Basket Analysis (Association Rule Mining)}\\
\textit{SQL tunning and designing parallel queries for data definition and manipulation}
}
%------------------------------------------------
\skillgroup{Software Engineering Skills}
{
\textit{Programming and Scripting Languages: Python, Perl, Java, Awk, Shell, C, C++, LISP,ASP.NET, C\#, VB.NET}\\
\textit{(Toolboxes: MATLAB, Octave, PRTOOLS, VLFEAT, CLOP}\\
\textit{Database Management Systems: Oracle, MSSQL, PostgreSQL MySQL, Infobright}\\
\textit{Source version control: Mercurial, git}\\
\textit{Excellent knowledge in working with windows and Linux/Unix platforms}
}
%------------------------------------------------
\skillgroup{Soft Skills}
{
\textit{Proficient in using Microsoft Office suite applications }\\
\textit{Excellent communication, leadership, interpersonal and pedagogical skills}\\
\textit{Management skills and ability to work with a team }\\
\textit{High level of motivation and self-drive}
}
%----------------------------------------------------------------------------------------
% EMPLOYMENT HISTORY SECTION
%----------------------------------------------------------------------------------------
\section{Work Experience}
\job
{Aug 2016 -}{Present}
{Tiaxa, Germany}
{http://www.tiaxa.com}
{Data Scientist}
{
\begin{itemize-noindent}
\item{ Use all available data, undertaking data discovery and exploration to identify opportunities, develop strategies and techniques to improve results}
\item{ Model and frame meaningful business scenarios that impact on critical business processes and/or decisions}
\item{ Design, develop and evaluate innovative models for predictive learning}
\item{ Develop tools for complex statistical analysis using Python, R and MATLAB}
\item{ Apply advanced statistical and predictive modeling techniques to build, maintain, and improve on multiple real-time decision systems}
\item{ Translate technical details, observations and results into business language}
\item{ Engage with project owners regularly to review project results, improve quality and satisfy all project requirements}
\end{itemize-noindent}
}
\job
{Sep 2013 -}{July 2016}
{Tecnotree Corporation, Espoo, Finland}
{http://www.tecnotree.com}
{Consultant SEA Region (Telecom Billing)}
{
{Scope of Service}\\
\textbf{Roaming and Interconnect}
\begin{itemize-noindent}
\item{ Completely responsible (end to end) for activities undertaken as part of the Support team}
\item{ Carrying out TADIG (IREG) testing for new operators configured}
\item{ Issuing TAP certification on completion (TCC) of the testing phase with the operators}
\item{ Co-coordinating with the DCH (Data Clearing House) for the Transfer of TAPIN, TAPOUT files and RAP dispute }
\item{ Ensuring Files are transferred to DCH on time and daily checking of TAPIN Missing and Ageing files}
\item{ Trouble shooting of TAPIN and Switch files rating errors occurred during the rating process }
\item{ Reconciliation of TAPIN and TAPOUT files }
\item{ Troubleshooting the issues and recycling the Rejects and wrong rated CDR’s for Roaming and Interconnect Partners}
\item{ Configuration of Roaming and Interconnect Partners}
\end{itemize-noindent}
\textbf{Loyalty and Campaign Management}
\begin{itemize-noindent}
\item{ Configure and launch Campaigns}
\item{ Monitor Campaigns, Pre-rating process, Rating}
\item{ Ensure reports are extracted and published in a timely manner}
\item{ Monitor rejections and clear them}
\item{ Support for patch movement}
\item{ Monitor and ensure redemptions are done without any delays}
\end{itemize-noindent}
\textbf{General MSO Activities}
\begin{itemize-noindent}
\item{ Work on aggressive time lines }
\item{ Handle Emergency/Critical Situations and Escalations }
\item{ Ensure that On site Support is done in a timely and efficient manner}
\item{ Adhere to Quality Life Cycle }
\end{itemize-noindent}
}
%------------------------------------------------
\job
{Mar 2013 -}{Sep 2013}
{Uganda Telecom, Kampala, Uganda}
{http://www.utl.co.ug}
{Business Analyst and Retention Manager}
{
\begin{itemize-noindent}
\item{ Play key role in developing UTL retention strategy}
\item{ Reduce monthly churn rate, enhance customer life cycle value}
\item{ Implement Micro-Segmentation for UTL customers for identification of revenue streams and maintain and increase customer life cycle value }
\item{ Identify and monitor Telecom industry trends (New Sales, Churn, Reactivations, Market Share) and provide comprehensive business intelligence for new products}
\item{ Manage development and delivery of KPI aligned reports, dashboards and ad-hoc analysis for commercial team}
\item{ Formulate channel strategies, and along with designing performance scorecards (based on proven models)}
\item{ Develop forecasting models for Churn, Sales and Revenue projections}
\item{ Develop customer relationship strategies; test new concepts (“Above the Lin Line”)}
\item{ Segment/Profile customers for loyalty, retention, upsell, cross sell and revenue enhancement}
\item{ Manage Micro Segmentation campaigns, pre and post and Return on Investment Analysis}
\item{ Design and develop ‘information models’ which are user-centered interfaces allowing rapid access to contextual information}
\item{ Integrate information points (data analytics, market research and market intelligence) to produce insights on customer and market behaviour}
\end{itemize-noindent}
}
\job
{Sep 2012 -}{Feb 2013}
{Uganda Telecom, Kampala, Uganda}
{http://www.utl.co.ug}
{Business Intelligence Developer}
{
\begin{itemize-noindent}
\item{ Designing, planning and implementing BI solutions}
\item{ Debugging, monitoring and troubleshooting BI solutions}
\item{ Creating and deploying business reports using Microsoft Business Intelligence Suite (SSRS)}
\item{ Writing relational and multidimensional database queries for different Database Management Systems (MSSQL, MySQL(Infobright) and Oracle)}
\item{ Perform analysis and integration services using Microsoft Business Intelligence Suite (SSAS and SSIS)}
\item{ Market Basket Analysis (Association mining) –to identify common item sets and rules for cross-selling}
\item{ Classification and Regression}
\item{ Clustering for market micro-segmentation}
\item{ Forecasting}
\item{ Sequence and Deviation Analysis}
\end{itemize-noindent}
}
\job
{Jan 2011 -}{Sep 2012}
{Uganda Telecom, Kampala, Uganda}
{http://www.utl.co.ug}
{Interconnect Billing and Roaming Data Analyst}
{
\begin{itemize-noindent}
\item{ Processing and reconciling CDRs with the switch/network element statistics}
\item{ Modifying and implementing the Business rules and initiating change requests for mediation}
\item{ Carry out advanced CDR analysis and investigation}
\item{ Perform Returned Account Procedure(RAP) file processing}
\item{ Clearing suspense/rejected CDRs and (re)submitting them to the Billing system for (re)rating}
\item{ Establishing, implementing and reporting on the interconnect mediation revenue assurance controls (RACs)}
\item{ Ensuring timely completion of Transferred Account Data Interchange Group (TADIG) tests after IREG tests}
\item{ Monitoring of NRTRDE(Near Real Time Roaming Data Exchange) process for fraud detection}
\item{ Analyzing problems and incidents related to the billing system, SMS-C, and MSCs and other connected network elements on a daily basis}
\item{ Analyzing and resolving roaming related issues/tasks on a daily basis}
\item{ Submission of accurate and timely interconnect billing and roaming reports}
\item{ Identifying, analyzing and resolving or escalating system issues to vendors}
\end{itemize-noindent}
}
\job
{Jan 2010 -}{Jan 2011}
{Orange Uganda Limited now Africell, Kampala, Uganda}
{http://www.orange.ug}
{Roaming and Interconnect Administrator}
{
\begin{itemize-noindent}
\item{Ensuring that all roaming Customer Details Records (CDRs) are sent to MACH (Clearing house) on a daily basis}
\item{Ensuring that Transferred Account Data Interchange Group (TADIG) tests were completed within one day after IREG tests}
\item{Monitoring of NRTRDE (Near Real Time Roaming Data Exchange) process for fraud detection}
\item{Provision of daily and monthly interconnect reconciliation report to the Finance Department}
\item{Provision of High Usage Reports (HUR)}
\item{Administration and configuration of Interconnect Billing and Management system}
\end{itemize-noindent}
}
\job
{2009 -}{2013}
{Makerere University, Kampala, Uganda}
{http://mak.ac.ug}
{Part-time Lecturer}
{I conducted lectures, set, supervised and marked exam for the following courses to Computer Science students (Bachelors and Diploma) in Makerere University Department of Computer Science:
\begin{itemize-noindent}
\item{Numerical Analysis}
\item{Further Linear Programming and Network Analysis}
\item{Discrete Mathematics}
\item{Computer Literacy}
\item{Programming Methodology}
\item{Fundamentals of Mathematics}
\item{Computer Architecture}
\end{itemize-noindent}
}
\job
{2009 -}{2010}
{Kampala University, Kampala, Uganda}
{http://www.ku.ac.ug}
{Assistant Lecturer}
{I conducted lectures, set, supervised and marked exam for the following courses to Computer Science students in Kampala University School of Computer Science:
\begin{itemize-noindent}
\item{Computer Programming}
\item{Computer Literacy}
\item{Calculus I}
\item{Discrete Mathematics}
\end{itemize-noindent}
}
%----------------------------------------------------------------------------------------
% PROJECTS SECTION
%----------------------------------------------------------------------------------------
\section{Accomplished Projects}
\begin{itemize-noindent}
\item{I have managed to automate all Roaming, Interconnect and Loyalty Campaign related processes and reporting with in a period of one month after joining Tenotree Corporation}
\item{I was part of the team involved in the implementation of UTL Prepaid Commission Model, Churn, Prediction Model and Micro Segmentation of UTL’s Subscriber base}
\item{Implemented a real time raw CDR collector for prepaid UTL customers which resulted into timely, accurate reporting and support for running various promotions (awakening and activation bonus promotions)}
\item{Implemented a software solution using Perl to generate notification Tap files for UTL inbound roamers. This saved the company 40000 Euro that was required for regeneration of over 100,000 notification by the Clearing house}
\item{Implemented a software solution using Perl to correct billing information for RAPs (Rejected Tap files for UTL inbound roamers)}
\item{Implemented a raw CDR decoder using Perl for MSC (mobile switch)}
\item{Managed to resolve major Tap file exchange challenges between UTL and Data Clearing House (DCH). This helped the company to recover from huge revenue losses that were caused by files aging before reaching the DCH. This was achieved by implementing a number of controls and quality checks like successful ftp delivery reports}
\item{I was involved in the design, analysis and implementation (using python) of UTL bonus airtime model which came in handy during a number of acquisition campaigns}
\item{Implemented the good number algorithm in python for classification of UTL free number pool}
\item{I implemented a Near Real Time Roaming Data Exchange (NRTRDE) solution for roaming fraud detection using python which save UTL over 100,000USD that was to be charged by the vendor to implement the same solution. Solution is still being used by UTL}
\end{itemize-noindent}
%----------------------------------------------------------------------------------------
% IT/COMPUTING SKILLS SECTION
%----------------------------------------------------------------------------------------
\section{Key Competencies and Skills}
\skillgroup{Data Science}
{
\textit{Excellent scripting skills in Python, Shell and Awk for advanced huge data manipulation}\\
\textit{Proficient in Machine Learning, Artificial intelligence, Data Mining, Data Warehousing and Data Modeling}\\
\textit{Practical knowledge in applying machine learning techniques to implement Forecasting, Classification and Regression tasks}\\
\textit{Knowledge of Data Visualization tools like QlickView and Tabluea}\\
\textit{Working knowledge in Big Data technologies - Hadoop, Hive, Pig and Flume}\\
\textit{Proficient in Microsoft Business Intelligence Suite (SSRS, SSAS and SSIS)}\\
\textit{Proficient with Microsoft SQL Server 2008/2012} - database architecture and administration\\
\textit{ETL development using SSIS and Talend Open Studio}\\
\textit{Clustering for market micro-segmentation and Market Basket Analysis (Association mining)}\\
\textit{SQL tunning and designing parallel queries for data definition and manipulation}
}
%----------------------------------------------------------------------------------------
% RESEARCH GROUPS (Membership)
%----------------------------------------------------------------------------------------
\section{Research Groups (Membership)}
\interestsgroup{
\interest{Artificial Intelligence in the Developing World (AI-Dev)}
\interest{TADIG (Transferred Account Data Interchange Group)}
\interest{NRTRDE(Near Real Time Roaming Data Exchange)}
\interest{Mobile Roaming}
\interest{Interconnect/ Inter Carrier/CABS Billing}
}
%----------------------------------------------------------------------------------------
% REFEREE SECTION
%----------------------------------------------------------------------------------------
\section{Referees}
\parbox{0.5\textwidth}{ % First block
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{\bf Name} \> Dr. Washington Okori \\ % Referee name
{\bf Company} \> Tech Manhindra\\ % Referee company
{\bf Position} \> Director Projects \\ % Referee job title
{\bf Contact} \> Mob: +256 772 712 048 % Referee contact information
\end{tabbing}}
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\begin{tabbing}
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\> Dr. Ernest Mwebaze\\ % Referee name
\> Makerere University \\ % Referee company
\> Lecturer \\ % Referee job title
\> Mob: +256 772 121 272 % Referee contact information
\end{tabbing}}
%----------------------------------------------------------------------------------------
\end{document}