Mansour T Shams (US Citizen)

Chicago, IL

Cell: 847-***-****

Web: https://www.linkedin.com/in/mansourshams/

Email: adgx5x@r.postjobfree.com

PROFESSIONAL SUMMARY

Managed data science in industries such as Finance, Healthcare Medical Devices, Electronics, Telecommunications, Automotive, Food Services, Travel, Oil and Gas, and Facilities. Utilized full-stack analytical components such as Big Data, Stochastic Modeling, Data Warehouse, Data Lake, Data Mart, Data Schema optimization, MongoDB, JSON API, BSON, Node.js, Neo4j, Cypher, NoSQL, Excel, SQL, VBA, SAP, R, Python (NumPy, Pandas, Matplotlib, Seaborn, Plotly, Cufflinks, Scikit-learn, Panda Series, Panda DataFrames, Panda Time Series, Regular Expressions, NLP NLTK tokenization, tableau, and time-series.

EDUCATION

• PhD and Master’s, Computer Engineering, Queen’s University, Canada: Stochastic modeling, Probability Theory, Queuing Theory, Discrete Event Simulation, Monte Carlo Simulation, Simulation and mathematical modeling, Artificial Intelligence (AI)

• MBA in Project Management, George Washington University School of Business

• Bachelor degree in Computer Engineering, The University of British Columbia, Canada

• Lean Six Sigma Master Black Belt Certification, Motorola, USA

• Experience with Cloud, Java Script, Programming Paradigms, Big Data, Finance, Tableau, and Time Series BP, Feb 2019 to Present, Data Science Product Manager

• Managed Products with Neural Networks, Tensorflow, Keras, Big Data (hadoop, HDP cloudera, hive) and Multivariate platforms affecting Strategic and Tactical Level KPIs reporting across SQL, NoSQL, and Azure

• Data Warehouse strategic alignment and optimization with respect to Reporting, AI, Customer Insight services, and organizational KPIs and KRIs

• Hadoop and SQL architecture with Alteryx and Pega

• Utlized cloud computing with Google Cloud, Yahoo Cloud, iCloud, Microsoft Cloud, and Adobe Cloud (IaaS, PaaS, SaaS), utilizing Cloud Cost Reduction, Reliability, Efficiency, Security, and Operational Excellence

• Produced Data Architecture Specification and Architectural Design describing processes, tools, technologies, platforms, and policies to allow the provision of services

• Executed Data Governance principles of Transparency, Accountability, and Standardization in the areas of Policy, Quality, Compliance, and Business Intelligence

• Utilized Amazon Web Services (AWS), Data Warehouse, Data Lake, Data Mart, SQL, JSON, SaaS, UiPath, RPA, NoSQL, KDB+, Neo4j (Intuitiveness, Speed, Agility), Graph Engine, Cypher, Schema efficiency, MongoDB, MongoDB Script, Cassandra, Entity Relationship, and Graph Database on Big Data, Retail Recommendation Systems, Recommender Systems, Javascript, Scala, Access, Excel, relational databases, machine learning, artificial intelligence, Social Graph, Interest Graph, Consumption Graph, Location Graph, and Intent graph, GraphXR, Big Data Analytics, Stochastic Time Series, R and Pyton algorithms, SciPy ecosystem, SciKit, SciKit-learn, Pandas, Seaborn, plotly, cufflinks, Numpy, opencv, KNN, K-Nearest Neighbor, Ridge regression, Support Vector Machine, Tensorflow, K means, Pytorch, NLP, NLTK, Python software unit test, ETL, and NLP to achieve Customer Excellence

• Implemented data driven continuous improvement, operational excellence, Software Development, Research & Development, Statistical Consulting, Financial Modeling, root cause analysis to enhance Financial Operations

(FinOps), sales forecasting, Customer Satisfaction, Process Efficiency and Utilization, Market share, SalesForce product Risk Management, COGS and Contra COGS

Accenture, Feb 2017, Feb 2019 Master Black Belt and Data Scientist(2 years contract)

• Providing and delivering predictive Analytics, Prescriptive Analytics, Hypothesis Testing, and Price Demand modeling in the context of Business Intelligence and Big Data Science utilizing Algorithms, ETL (Extract, Transform, Load), Data Mining, Data Insights, Minitab, SPS,, Excel, Portals, Dashboards, DOE, statistical methods, density and distribution functions, time series, stochastic processes, stochastic volatility, Regression Models, Monte Carlo Simulation, Discrete Event Simulation, ANOVA, T-test, Pivot Charts, Pareto Charts, Pivot

• Table, VBA, SQL, C, C++, R, Jupyter, Python, Vlookup, Control Charts, Hoshin planning, and Bayesian Statistics

• Utilized Python Machine Learning, Data Splitting, Multivariate Regression modeling, Decision Tree, Random Forest, Adjusted R-squared, Logistic Regression, numpy, pandas, Bayesian Statistics, Natural Language processing, DAX, powerpivot, power pivot, Power BI, Tableau Dashboard Visualization

• KPI improvement, operational risk assessment, operational risk score reduction of +30%, and +$100,000 cost reduction. In excess of 40 projects in parallel, with project management, team management, and TFM metric utilizing the JDA Software

• Monitoring and tracking projects and providing data model validation in comparison with the historical data Sodexo IMF INC., Washington, DC Jan 2015 TO Feb 2017 Director of Business Operations & Transformation ( 2 Years Contract) Operational Excellence and Data Analytics

• Responsible for developing data models, statistical models and data research to provide real-time analytics and visualization for forecasting of the cost reduction and quality improvement projects to improve reliability, improve customer satisfaction.

• Pricing time-series predictive modeling with Tableau

• Python Machine Learning, Data Splitting, Multivariate Regression model building, Decision Tree, Random Forest, Adjusted R-squared, Logistic Regression, numpy, pandas, Bayesian Statistics, Natural Language processing, DAX, Go Programming Language, distributed systems, data structures, Linux, Unix, Node.js, powerpivot, power pivot, Tableau Dashboard Visualization • Achievements (Public Trust Clearance):

• Attaining perfect 100% KPI, and implementing numerous cost saving initiatives

• Reducing the Value at Risk and operational risk defined in the contract through Monte Carlo simulation

• Asset Management Framework (AMF) analytical deployment to match the client's best in class and maintenance strategy through facilitation, consulting, and e-discovery utilizing Google Cloud to improve CMMI

• Health Safety and Environment (HS&E) best in class implementation with risk analysis and corrective/preventative root cause analysis to attain the highest KPI

Achievements (Public Trust Clearance):

• Attaining perfect 100% KPI, and implementing numerous cost saving initiatives

• Reducing the Value at Risk and operational risk defined in the contract through Monte Carlo simulation

• Asset Management Framework (AMF) deployment to match the client's best in class and maintenance strategy through facilitation, consulting, and e-discovery utilizing Google Cloud to improve CMMI

• Health Safety and Environment (HS&E) best in class implementation with risk analysis and corrective/preventative root cause analysis to attain the highest KPI

• ISO55000 Asset Management Framework

• Hoshin strategy deployment and Shingo Value Stream Mapping EASTEK INTERNATIONAL, LAKE ZURICH, IL MAY 2013 TO JANUARY 2015 GLOBAL DIRECTOR OF QUALITY SERVICES, OPERATIONS, TRANSFORMATION, AND CONTINUOUS IMPROVEMENT

• Systematic CPG product (software and hardware) quality third party outsourcing risk assessment, risk management utilizing Probability and Impact Matrix, SWAT, FMEA, Production Part Approval Process (PPAP), Advanced Product Quality Planning (APQP), and Risk Score to avoid, mitigate, transfer, or accept risk and building of RISK matrix into the ERP system to flag high risk score parties

• Carried out and directed global quality and reliability based on supplier’s processes data and field data (from Internet of Things (IOT), etc) for products in medical, automotive, and food industries leading to warranty cost reduction and customer satisfaction improvement in ISO9001, ISO13485, and CMMI utilizing PPAP, Predictive Analytics, Prescriptive Analytics, Hypothesis Testing, and Price Demand modeling

• Python Machine Learning, Data Splitting, Multivariate Regression, Polynomial Regression model building, Decision Tree, Random Forest, Adjusted R-squared, Logistic Regression, numpy, pandas, Bayesian Statistics

• Utilized SharePoint to construct CMS Sites and the flows as a central repository for Vision, Charter, and improvement initiatives

• Language processing, deep learning, DAX, powerpivot, power query, Tableau Dashboard Visualization, matlab

• Managed reverse logistics for medical, automotive, and food processing control products utilizing Google Cloud within the context of Net Promoter Score (NPS) itself implemented in the context of global continuous improvement program

Achievements:

• 30% Labor reduction through automation, process VSM, and process based QC

• Attaining product reliability by lowering the defect rate to below 0.01% and leading FDA Audits

• Automated medical device big data gathering and reliability analysis (big data, data warehouse, data warehousing, data mining)

• Attaining and maintaining 98.5% customer satisfaction through facilitation, consulting, and e-discovery (including cleanroom environment)

• Utilizing Robotic Process Automation (RPA) to transit to new ERP to carry out analysis on the manufacturing floor process

SNAP-ON TOOLS, KENOSHA, WI APRIL 2009 TO APRIL 2013 GLOBAL RAPID CONTINUOUS IMPROVEMENT

• $3B automotive and Aerospace manufacturer and marketer of tools, equipment, SaaS diagnostics, Agile software/ hardware development and coaching, repair information, and systems solutions

• Managed reverse logistics, inspections, program management metrics, and CRM information feedback from customers to the CPG product design to attain best in class performance utilizing Predictive Analytics, Prescriptive Analytics, Hypothesis Testing and Price Demand modeling

• Systematic product (Agile Java Development Environment) quality third party outsourcing risk management utilizing Probability and Impact Matrix, SWAT, PFMEA, and Risk Score to avoid, mitigate, transfer, or accept risk

• Owned global automotive Quality Management System (QMS), Change Management, as well as Rapid Continual Improvement implementation based on Toyota production systems (Toyota’s Kaizen and Shingijutsu approaches) implemented in China, North America, and Europe with best in class HS&E with no incident occurrence, published white papers

• Improved quality and reliability by 30% to 100% at each initiative utilizing Google Cloud

• Python Machine Learning, Data Splitting, Multivariate Regression, Polynomial Regression model building, Decision

• Tree, Random Forest, Adjusted R-squared, Logistic Regression,, numpy, pandas

• Identified and interpreted KPIs as well as strategic Cost, Quality, and reliability, metrics into daily operations at Sales

• & Marketing, Software Evaluation for new releases, Operations, and Engineering (utilized A3, Heijunka, Jidoka, Kaizen, Hoshin Strategy, Oracle ERP, MRP, data analysis, data warehouse, data warehousing, and SAS) Achievements:

• Completion of five Continuous Shingijutsu or Kaizen events per quarter measured in terms of financial and CMMI results

• Annual $1M Cost reduction and $1M of cost avoidance

• Attaining and maintaining 98% customer satisfaction or better utilizing facilitation, consulting, and e-discovery with all divisions of the organization

MOTOROLA, SCHAUMBURG, IL 1998 – 2009 SENIOR QUALITY AND SIX SIGMA MASTER BLACK BELT

• A $33B Automotive and Telecommunications CPG products in a range of automotive, digital communication, and entertainment services (DoD)

• Reported to Quality VP in high volume SaaS, and precision manufacturing environment utilizing Agile and waterfall Java Development Environment, C and C++

• Utilized DFSS, machine learning, time series, and IDOV in the design stage to correct process reliability and failures to ensure low rate of manufacturing defect and customer dissatisfaction

• Systematic product (hardware) quality third party outsourcing risk assessment, risk management utilizing Probability and Impact Matrix, SWAT, FMEA, and Risk Score to avoid, mitigate, transfer, or accept risk, published white papers

• Carried out model validation for stochastic, simulation, and statistical models as well as Internet of Things (IOT) and algorithm designs with Witness and Simulink

• Carried out Waterfall and Agile software evaluation based on the Requirements and statistical results of the test outputs, inputs being mechanical, electrical, or software, test subjects being handheld devices, databases, and ERP

• Managed Product Quality, Reliability, stress testing, and Customer Satisfaction (within the context of Net Promoter

• Score (NPS)) by implementing VOC surveys and customer dissatisfaction root causing as well as DMAIC approach to streamline processes, reduce cost, increase revenue, and improve customer satisfaction KPIs leading to reduction in the detractors and increase in the promoters Achievements:

• Executed DFSS and CMMI projects in the context of Kaizen Events in operational and transactional domains

• Trained Six Sigma Master Black Belts, Black Belts, and Green Belts

• $20M inventory and operations reduction of a $200M Supply Chain materials and procurement

• Attained 98.5% on time delivery JIT and customer satisfaction through automation for labor reduction and on time delivery, facilitation, consulting, and e-discovery with all organizations, utilizing JMP, SAS, and Minitab GOVERNMENT OF CANADA, OTTAWA, CANADA, 1996 – 1998 RESEARCH CONSULTANT (2 YEAR CONTRACT)

• NRC is the Government of Canada's premier research and technology organization

• Managed and established cross-functional departmental interactions of the services, and providers

• Researched and benchmarked new products, services, competitive information, and standards

• Developed metrics on ROI to determine business expectations, published white papers

• Analyzed complex production processes using common process utilization techniques

Contact this candidate