Ed Mwanza
Tech. Lead Data Scientist at Boeing Intelligence & Analytics- Claim this Profile
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Bio
Credentials
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Self-Driving Car Engineer
UdacitySep, 2021- Nov, 2024 -
Deep Learning Specialization
CourseraFeb, 2018- Nov, 2024 -
Sequence Models
CourseraFeb, 2018- Nov, 2024 -
Convolutional Neural Networks
CourseraNov, 2017- Nov, 2024 -
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
CourseraSep, 2017- Nov, 2024 -
Neural Networks and Deep Learning
CourseraSep, 2017- Nov, 2024 -
Structuring Machine Learning Projects
CourseraSep, 2017- Nov, 2024
Experience
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Boeing Intelligence & Analytics
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United States
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Defense and Space Manufacturing
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300 - 400 Employee
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Tech. Lead Data Scientist
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Mar 2018 - Present
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Capstone IT
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United States
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IT Services and IT Consulting
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1 - 100 Employee
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Senior Data Scientist
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Feb 2018 - Mar 2018
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Union Pacific Railroad
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United States
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Rail Transportation
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700 & Above Employee
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Lead Data Scientist
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Jan 2017 - Jan 2018
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Monsanto Company
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United States
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Farming
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700 & Above Employee
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Data Scientist
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Apr 2016 - Aug 2016
• Worked on a diverse, cross discipline team to build a precision product placement model • Designed and developed business-ready dashboards/visualizations using R, Python, Spotfire and Pipeline Pilot. • Converted ideas and business needs into data requirements to support R&D analytics efforts. • Wrote queries using SQL (PL/SQL) to extract and manipulate data to achieve desired results using select statements, sub-queries, joining multiple tables, scripting. • Performed descriptive and predictive data analytics using R or Python and Spotfire. • Designed predictive models for enterprise day-to-day applications using machine learning techniques. • Retrieved external open-source data using APIs, R/Python or pilotscript when needed. • Involved in data migration efforts from Oracle database to the Cloud (AWS) • Performed data integration and automation using Jenkins, Github and Spotfire. • Automated data pulling jobs to get live data for real-time KPI metrics. • Collaborated with other teams in the data pipeline to achieve desired goals. • Managed and maintained field observations dashboards capturing pre-plant through harvest metrics such as irrigation-methods utilized, tillage-type, nitrogen application type, nitrogen application time, field/plot dimensions, crop density, soil types etc., up-to and including harvest to characterize a field and gain insight on the impact of various environmental and field management factors. Show less
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Chevron
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United States
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Oil and Gas
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700 & Above Employee
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Data Science/Data Engineer/Performance Group
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Jun 2012 - Oct 2015
• Performed predictive data analytics using machine learning techniques to optimize operations for offshore deep water and onshore shale drilling. • Conducted research using quantitative methods to model drill string failure due to down-hole vibrations. • Contributed and reported initiatives using data discoveries to support enterprise engineering community achieve value based objectives. • Performed data discoveries to extract patterns and trends and developed business use cases using tools such as R, Spotfire and/Tableau, SQL that provided insights in decision making. • Queried & analyzed huge volumes of complex operations data to drive key performance metrics that drove actionable insights. • Directly involved in ETL projects for enterprise data. • Member of the operational excellence team driving performance efforts. • Created and maintained quarterly and annual performance metrics for three (3) Business Units using Spotfire or Tableau • Performed quarterly data quality scoring for optimal business units’ performance evaluation across the enterprise . • Assisted reviewing corporate operational Standards of Procedures (SOPs). • Database administrator for Rushmore drilling and completions for unconventional resources. • Validated deliverables per project and/or contract requirements. • Team contributor to enterprise reservoir assets management team. Show less
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Education
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Missouri University of Science and Technology
Doctor of Philosophy - PhD student, Computer Vision & Machine Learning -
Missouri University of Science and Technology
Master’s Degree, Computer Science -
Missouri University of Science and Technology
Bachelor’s Degree, Petroleum Engineering