Sandeep Rajput



Sandeep RajputEmail: sandeep_rajput@ Phone: (425) 449 9554 [Cell]Web: Professional Summary13 years in Predictive/scientific analytics development and management in Industry; 5 in academia5 years team management 4-8 FTEs and 20-30 contractors distributed globally; 8 years as team leadKnowledgeable about classical and modern tools and technologies (C++, SAS, SQL to Java, R, Hadoop)Professional Experience2010—2013 Principal Data Scientist & Group Product Manager (Monetization), Microsoft Data ScienceBuilt models and algorithms to flag harvested or pirated Win7 license keys worldwide from large data. Modeled and identified signatures of piracy for several licensing channelsDigital AdvertisingLed keystone projects to unlock advertiser demand on adCenter (aka Bing Ads) by 40-60% through specific bid, keyword and campaign guidance at scale through scientific analysis of massive dataBig DataCreated demand and supply slices via data mining on Bing Ads monetization data; modeled revenue displacement and other metrics for effective use of marketing resources2003—2010 Senior Research Scientist Lead, Fair Isaac Corporation (FICO) Predictive ModelingBuilt suites of models (regression, neural networks, additive models) to predict delinquency, likelihood to pay, revenue, profit, attrition, payment card and e-commerce fraud for clients in North America, Europe and Middle East; advised on optimal strategies for these outcomesMachine LearningDeveloped feature libraries of consumer preferences from time-series and textual information, predictive models with these features helped generate new line of revenue Prod. DevelopmentApplied R&D evaluating alternate predictive algorithms, feature selection methodologies and using multiple scores to optimize customer lifetime value; implemented model monitoring schemesData MiningDesigned the 2009 FICO/UCSD Data Mining Contest (304 teams from 35 countries contested)Co-founded the internal wiki on predictive modeling for training and reference; served as subject matter expert on predictive modeling process, from data summary to post-deployment activities Retail BusinessConsulted to optimize store location and targeting; analyzed campaign performance; built direct marketing response/conversion models; helped optimize product offerings 1996—1998 Assistant Manager (Projects), Reliance Industries Limited Tech. ProgramManaged the revamp of a Polyester Staple Fiber (PSF) plant to double production; created equipment specs, supervised technical output of vendor engineers; designed the DCS dashboardModeling/SimulationTechnical consulting for executive engineers; created math models to fit observed measurements, simulated control strategies to help reduce downtime and accidental shutdown1998—2003 Grad. Research Assistant, Measurement and Control Engineering Center Scientific ModelingDeveloped a Matlab toolbox to track small particles in fluidized beds from videos/movies to characterize the velocity fields; compared experimental output with CFD simulationsData ScienceConsulted with large chemical companies for fault diagnosis and monitoring via nonlinear time-series analysis; Developed GUI software package for nonlinear time-series analysis in Matlab; held workshops for industry attendees, created training material and manualsEducationPh.D.Chemical EngineeringThe University of Tennessee, Knoxville1998—2003M.S. StatisticsThe University of Tennessee, Knoxville2002—2003 B. S.Chemical EngineeringIndian Institute of Technology, Kanpur, India1992—1996Technical SkillsProgrammingC++, Java, Perl, Python, Scala, Fortran; Eclipse, NetBeans, Visual Studio; Subversion, MavenAnalysis Matlab, R, SAS, NumPy/SciPy/Pandas, Octave; LaTeX, Beamer; MS Word, Excel, PowerPoint, VisioBig DataApache Hadoop, Hive, Pig; Mallet, OpenNLP, Lucene/Solr; SQL Server, PostGreSQLModelingLinear, logistic and generalized regression; Generalized additive models; Bayesian modelsMachine LearningNeural networks, Clustering; Mixture Models; Random forests; Decision treesApplied Research2014Web users as Automatons with limited Sentience: a Physics-based model of user interaction.2013[w/Paul Smolikov] Segmenting Web users by informational needs: A case study on Bing users.Heavy tails in Online Experiments: Power laws and preferential attachment.Measuring scale in second-price auctions.2012Six tropes and the alignment of demand and supply.2011Search user intent and the primacy of local time.2010Modeling Search marketplace metrics with Robust AR models.2009Neural Networks and Special Values: Building better predictive models.2008Next Best Action: a Reinforcement Learning paradigm.2007Recursive profiling and its impact on model performance.2005Event-triggered marketing: reaching customers at the right time.2004Dynamic marketing strategy to detect customer lifestyle changes.Academic Research2004Sarnobat, S. U., Rajput, S., Bruns, D. D., DePaoli, D. W., Daw, C. S. and Nguyen, K. (2004). Impact of external electrostatic fields on gas-liquid bubbling dynamics. Chem. Eng. Sci. 59(1), 247—258.2003Rajput, S. and Bruns, D. D. (2003). Nonlinear time series analysis of flooding in a distillation column, Paper 465d, in Proc. AIChE Annual Meeting 2003. ISBN 0-8169-0941-5Rajput, S. and Bruns, D. D. (2003), Principal Curves and Chaos, AIP Conf. Proc., 676(1), 327-332.Rajput, S. and Bruns, D. D. (2003). Numerical simulations of the fluidized bed experiments using MFIX multiphase CFD code. Report for Oak Ridge National Laboratory, ORNL-400002312Rajput, S. and Bruns, D. D. (2003). Detection of Velocity Fields from videos of particles in fluidized beds. Report for Oak Ridge National Laboratory, ORNL-400002312.2002Rajput, S. and Bozdogan, H. (2002). Choosing the number of PCs in localized PCA using kernel smoothing and information-theoretic criteria. Report for Statistics Dept., UT Knoxville.2000Rajput, S., Shul-Cloper, R., Abidi, M. A. and Gonzalez, R. C. (2000). A new method for searching an image in a scene. Report for IRIS Lab, Elec. & Comp. Eng. Dept., UT Knoxville. ................
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