Thomas Joseph is a Head of Data Science and Analytics with over a decade of hands-on experience building AI, ML and data products, currently leading data science at WPP Production (Hogarth Worldwide). He has a strong track record scaling analytics practices across consulting and enterprise environments—from Wipro and Aspire Systems to Saksoft—and has authored multiple Packt publications on deep learning and data science. His background spans research-grade experimentation (recommenders, NLP, image recognition, time series) through to production deployment and team-led delivery, reflecting both technical depth and business-facing leadership. Based in Tamil Nadu, India, Thomas combines an MBA from IIT Delhi with engineering roots, and contributes to community learning (e.g., Packt’s interactive Data Science Workshop notebooks), signaling a commitment to practitioner education as well as product impact.
10 years of coding experience
13 years of employment as a software developer
Indian Institute of Technology Delhi (IIT Delhi)
Bachelor of Technology (B.Tech.) Civil Engineering, Bachelor of Technology (B.Tech.) Civil Engineering at NSS College of Engineering
PGDIACM Construction Management, PGDIACM Construction Management at NICMAR
A New, Interactive Approach to Learning Data Science
Role in this project:
Data Scientist
Contributions:177 commits, 1 PR, 104 pushes in 3 months
Contributions summary:Thomas contributed by uploading two .ipynb files, Chapter03/Activity_3_1.ipynb and Chapter03/Activity_3_2_Logistic_Regression_with_Feature_Engineering.ipynb. The user added code and installed necessary packages to the files using pip install. This implies the user has focused on working on the Data Science Workshop by Packt Publishing to learn Data Science in detail.
Contributions:2 pushes, 1 branch in 4 years 2 months
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