Rich Lysakowski
Network Technology Academy Institute
Data Science Program Leader
Greater Boston Area
I was trained as a real lab scientist (physical and analytical chemistry) long before data science was conceived. Although I started using Python more than 15 years ago, I jumped in to focus on learning "data science" about 3 years ago, shifting over from Business Intelligence, Analytics, and reporting.
I work as a Hands-On Trainer for Python and all things Data Science.
AREAS OF KNOWLEDGE:
• Scientific R&D, Lab, and Financial Informatics and Business Intelligence
• Bioinformatics tools and NGS data analysis pipelines
• Data Science (Data Visualization, Munging, Statistical Machine Learning, and Deep Learning)
• Systems Implementation, Validation (GxP), Testing, Administration
• ELN & LIMS User Training, Documentation, and Support
• Business Analysis, System Selection, Integration
• IT Project Management
TECHNICAL SKILLS:
• Python Tools and Frameworks (PANDAS, Numpy, SciPy, matplotlib, Scikit-learn, TensorFlow)
• R / RStudio
• Tableau
• Oracle 11g / 12c PL-SQL Dev / DBA
• C# Visual Studio 2015 and MS.NET 3.5+
• MS-BI Stack (PowerBI Desktop, PowerPivot, SS*S, Data Warehousing)
• WPF, WinForms, ADO.NET, Entity Framework
• MS T-SQL and SQL Server 2014 DBA
• Java on Eclipse
• VB6 thru VB 2012
• Lab Automation
• Analytical Instrument Design/Fabrication
• Machining and Electronics
Specialties: Programming in Python, SQL, Excel VBA, R, actionable statistics, dynamic visualizations in Tableau, data standardization / formatting / validating.
I take the position that data science can be real science -- rather than a pseudo-science, big data engineering, marketing hype or management consulting "hype" -- IF AND ONLY IF people follow a rigorous scientific methodology that validates their hypothesis. People must learn to distinguish between activities that are scientific in methodology, and something else. If you read this far in my profile, then you are inquisitive, TALK TO ME.