Data Scientist
Boeing
Total des années d'expérience :27 years, 10 Mois
conducted text and data mining, provides support for data analysis, data mining and predictive modeling techniques to extract analytics and insights from a variety of sources including structured, semi-structured, and unstructured data, using in depth knowledge of data mining analytic algorithms utilizing the power of SPSS Modeler, to conduct data mining of several millions of records of datasets, in Big Data (in TB size) running on Teradata, and Hadoop Cluster. This includes running SQL queries, and table JOINS on Teradata warehouse.
•Worked within a cross-functional team at Boeing, made up of business owners, consultants, engineers, data scientist, IT professionals, data modelers, Big Data programmers (Hadoop and Map Reduce) as well as Business Intelligence designers and developers. As part of the team, as a data Scientist was able to develop highly robust Ensemble data mining models- such as Classification Decision Tree, CHAID, C5.0, CRT, SVM and Tree Augmented Naïve Bayes, Logistic regression, and Cox regression for Hazard and Survival analysis for Aircraft fleet components maintenance and reliability analysis.
Lead data scientists team at Applied Knowledge Science to conduct text and data miming modeling techniques utilizing SAS enterprise Miner, and SPSS Modeler, Hadoop, and Map Reduce Big Data Analytic tools to develop predictive model using data Segmentation, Clustering, Classification and Association machine learning algorithms to mine Millions of US patents and trade mark database records to analyze and predict the Small and Medium Enterprise (SME) sector innovation capability and productivity by size, sector, and intellectual capital (intangible asset market valuation). The adoption of the model is expected to increase the productivity of average SME firm by 10% at minimum.
Lead strategic data mining and analytic project to conduct Big Datasets, including sensors data, mining for Telecom. Giant state-owned Enterprise, at Abu Dhabi Security Exchange market, market sales data analysis and developed a predictive data mining customers’ Churn model, and advertise campaign prediction model. The outcome was a 20% increase in customers retention and sales, and 10% in stock value utilizing a host of analytic tools such as (SPSS modeler, R and SAS).
Teaches Economic, Math. Economics, Statistics, Int'l finance and Int'l Trade, Money & Banking
Worked within an interdisciplinary team of Researchers at Congressional Research Services of US Congress and developed Time Series forecasting model (AR -Integrated- MA -ARIMA model), using Box-Jenkins methodology to Money Supply measures (M1, M2) growth and Inflation five years ahead. Using SAS, R, and E-views. The data set contains millions of records from US treasury and US Census data.
Taught Statistics, and Econometric, at undergraduate and graduate levels. Conducted field research at the Center for African - American Study on demographics statistical data analysis (ANOV, Cross-tabulation, Variance-co-variance, Correlation factor, Regression coefficient) for young African American schooling enrollment data sets extracted from US Census data.
Ph.D. in Economics; Howard University, Washington D.C., May 2000, USA.
M.A. in Economics; Howard University, Washington, D.C., 1994, USA. Microsoft Certified System Engineer (MCSE), Microsoft Corporation, USA.
B.Sc. Economics and Social Sciences; University of Khartoum, Khartoum, Sudan 1988.