Hello,
My name is
Michael
Michael Natenzon
And I
Work in
Data Science
Academically Researched
NanoTechnology
Studied
Enterprise Risk Management
And I Also
Coded This Website
Graduate of The Johns Hopkins University
Senior Data Scientist
BS, Materials Engineering
MBA, Enterprise Risk Management
I transform data into analytical dashboards that help decision makers more easily navigate ambiguous questions and problems.
I also build web and decentralized web applications in my spare time
My Experience
Spans across various disciplines and work environments, ranging from building an online business to working with an international non-profit to helping a manufacturing company improve efficiency and a digital assets exchange reduce fraud.
My takeaway has been that every employee has the potential to create significant impact when provided access to the right information in a dynamic and explorable format.
API Ingestion and Data Aggregation
Integrated DataBricks and Keyvault into Azure SQL database infrastructure
Built and managed Python ETL pipelines in DataBricks
Aggregated and structured data from external APIs
Statistical Analysis and Machine Learning
Applied statistics and ML techniques including random forests, regression, and ensemble learning to identify patterns of unusual customer behavior for RMA and fraud analyses.
Performed cross-validation to test out of sample model performance and applied ROC/AUC analyses to fine tune parameters that optimize the tradeoff between true positive and false positive rates.
Dashboarding and Visualization
Converted the outputs of complex data transformations and analysis into concise, interactive dashboards in Looker and PowerBI.
Developed over 50 dashboards end-to-end across sales, marketing, customer support, fraud and manufacturing.
Business Experience
Recognized promising IP within a JHU research lab, pitched to the
inventor, and was hired to identify customers, develop a business
model, and create a commercialization strategy. The evidence-based
findings shifted the project's direction and led to new
responsibilities involving digital modeling with Solidworks® and
prototyping with 3D printers.
June 2018 – May 2019
Led a team of MBA candidates helping JHU inventors assess the patent
landscape and market feasibility of their medicalgrade brain scanner; the
prototype will now be designed with a focus on solving target customers’ core challenges.
January 2018 – May 2018
Recognized promising IP within a JHU research lab, pitched to the
inventor, and was hired to identify customers, develop a business
model, and create a commercialization strategy. The evidence-based
findings shifted the project's direction and led to new
responsibilities involving digital modeling with Solidworks® and
prototyping with 3D printers.
June 2018 – May 2019
Led a team of MBA candidates helping JHU inventors assess the patent
landscape and market feasibility of their medicalgrade brain scanner; the
prototype will now be designed with a focus on solving target customers’ core challenges.
January 2018 – May 2018
Led a team of MBA candidates helping JHU inventors assess the patent
landscape and market feasibility of their medicalgrade brain scanner; the
prototype will now be designed with a focus on solving target customers’ core challenges.
January 2018 – May 2018
Engineering Experience
Paired statistical analyses with various Python libraries to create a pipeline that
could extrapolate the performance metrics of candidate materials in real time, while their
properties were being recorded. This helped materials engineering PhDs optimize a series of
data handling steps, minimizing processing times from an hour to seconds.
September 2018 – May 2019
Prototyped components for industrial applications using Solidworks® and MakerBot 3D printers
September 2018 – May 2019
Led a team of four engineering students to leverage optimization tools in
MS Excel to improve the yield and the electrical properties of piezoelectric
nanowire arrays – used for applications in nerve implants and micro- power generators.
June 2016 – May 2017
Optimized the data cleansing and analysis process for researchers exploring
brain-to-computer interfaces by organizing and leading a
team that built a Python-based, EEG (electroencephalogram) brain signal processing pipeline.
June 2016 – December 2016
Founded a platform to connect university students
based on their courses, enabling for more diverse and effective study groups.
November 2014 – May 2015
Johns Hopkins University
Carey Business School
- Ethical Leadership
- Governance and Accountability
- Negotiation
- Power and Politics
August 2017 – May 2019
- Business Analytics
- Big Data Machine Learning
- Data Analytics
- Data Science and Business Intelligence
- Quantitative Methods
August 2017 – May 2019
- Foundations of Management and Organizations
- Effective Management
- Managerial Decisions and Behavior
- Management of Technology
- Managing Complex Projects
- Operations Management
- Solving Organizational Problems
- Strategic Communication
August 2017 – May 2019
- Entrepreneurial Ventures
- New Product Development
- Discovery to Market
- Innovation For Humanity
August 2017 – May 2019
- People and Markets
- Competitive Strategy
August 2017 – May 2019
- Financial Modeling and Valuation
- Financial Resources I
- Financial Resources II
August 2017 – May 2019
Johns Hopkins University
Whiting School of Engineering
- BioMaterials
- Electrical Properties of Materials
- Electrical Properties Lab
- Kinetics and Phase Transformations
- How Advances in Materials Science Shape the World
- Mechanical Properties of Materials
- Mechanical Properties Lab
- Structure of Materials
- Thermodynamics of Materials
August 2014 – May 2019
- Characterization of Materials
- Chemistry of NanoMaterials
- Micro/Nano Structured Materials and Devices
- NanoMaterials Lab
- NanoWire Undergraduate Research
- Senior Design Capstone Project
August 2014 – May 2019
- Calculus I
- Calculus II
- Calculus III
- NanoMaterials Lab
- Linear Algebra and Differential Equations
- Probability and Statistics for Engineers
August 2014 – May 2019
- Computation and Programming for Engineers
- Gigantic Calculators for Materials Engineering
- Neurological Data Design
- Neural Network Modeling for Learning, Language, and Cognition
August 2014 – May 2019
- Chemistry Lab I & II
- Materials Chemistry
- Organic Chemistry I & II
- Organic Chemistry Lab I & II
- Physics I & II
- Physics Lab I & II
August 2014 – May 2019
- Culture of the Engineering Profession
- Leadership and Management in Engineering
- Professional Communication for Science, Business, and Industry
August 2014 – May 2019