Statistical methods and machine learning techniques applied to challenging business problems, data science for business problems Proven ability to work on teams, effective communication, and leadership in managing collaborative projects Specialties: Mathematical and Numerical Modeling, Data Science, Scientific Computing, Numerical Methods, Statistics, Optimization, Finite Element Analysis, C++, Matlab, Quantitative Analysis, Python, MySQL, SQL Server, Business intelligence, Sales Analytics, Data Mining, Machine Learning

Director of Algorithms and Analytics @ From June 2014 to Present (1 year 7 months) San Francisco Bay AreaDirector of Data Science @ Company Overview: Lattice Engines is the leader in B2B sales intelligence software enabling Fortune 500 companies to Sell Smarter and achieve a 6-14% increase in sales within one year of deployment through Intelligent Targeting, Contextual Conversations and Measurable Execution. Lattice Engines software integrates internal, external and Lattice Engines proprietary data to identify customer patterns and trigger events that influence buying decisions. Our software is powered by predictive analytics, advanced mathematical algorithms tuned specifically to B2B sales and marketing objectives. Our solutions integrate seamlessly with existing CRM and Marketing Automation systems to deliver B2B sales intelligence directly to your reps From February 2013 to June 2014 (1 year 5 months) San Francisco Bay AreaData Scientist @ - Lead data-driven analytical initiatives for SaaS solutions. - Data management and data manipulation - Performed customer profiling, market research, segmentation, statistical modeling and forecasting - Implemented Feature and Model Selection Algorithms using Information Theory - Improved modeling capabilities of Lattice solution enabling multiple machine learning algorithms and providing specific metrics to evaluate their performance From August 2011 to January 2013 (1 year 6 months) PostDoctoral Research Associate @ Collaborate with the Office of Naval Research (ONR) in research pertaining to high performance acoustic and elasto-acoustic modeling approaches and computational algorithm. Sponsored by the grant “High-resolution Computational Methods for the Solution of Direct and Inverse Acoustic Scattering Problems” Develop an original methodology for solving underwater acoustics and structural dynamics problems. Implementation of special finite elements that led to a computational cost reduction up to 20 fold Coding experience in large scientific computing projects; over 35k LOC in C/C++ and over 80k LOC in Matlab; some parallel, multicore and high performance computing experience From January 2007 to August 2011 (4 years 8 months) Lecturer @ Lectured an undergraduate class of 30 students on "Introduction to numerical methods" (40 hours). Led a student summer interim project From July 2009 to September 2010 (1 year 3 months) Teaching Assistant @ Collaborated on design and prepare the material for a PhD level class for Institute for Computational and Mathematical Engineering (ICME), Stanford University. Lectured classes From March 2009 to July 2009 (5 months) Scientific Consultant @ Petroleum System Modeling on High Performance Computing) Technological transfer of my PhD project to an industrial environment ENI R&D division From January 2003 to June 2006 (3 years 6 months)

Applied Mathematics, Mechanical Engineering @ Stanford University From 2007 to 2011 PhD, Mathematical Engineering @ Polytechnic of Milano From 2002 to 2006 M.Sc., Physics @ Università degli Studi di Genova From 1997 to 2002 Paolo Massimi is skilled in: Quantitative Analysis, Data Mining, Machine Learning, Mathematical Modeling, Numerical Modeling, Business Analytics, Matlab, B2B, Sales Analytics, Microsoft SQL Server, Numerical Analysis, Hadoop, Pig, Predictive Analytics, Price Forecasting