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- Company:
- Mphasis
- Job Title:
- Senior Manager
- Seniority:
- Manager
- Industry:
- IT
- Short Bio:
- Archisman Majumdar is senior manager at Mphasis Next Labs. At Mphasis, he conceptualizes, develops, and leads multiple products in the analytics R&D space. He is responsible for the research, innovation, and go to market for the products and solutions. Prior to Mphasis he has worked in Cognizant, Infosys, Siemens, and Wipro at various project management, research, and engineering roles.
Archisman completed his PhD from the Indian Institute of Management Bangalore (IIMB) in the Quantitative Methods and Information Systems area. He has published papers in various international conferences and was a visiting researcher at the IT University of Copenhagen during his PhD. His areas of expertise are in business analytics, social media, product management, and information systems research.
He lives in Bangalore with his wife and enjoys playing soccer and reading books.
- LinkedIn Profile:
- http://https://in.linkedin.com/in/archismanmajumdar
- Interests:
- Finding a new position, Networking, Recruiting
Archisman Majumdar's Blog
Domino habits for data science
Posted on September 19, 2017 at 10:30pm 0 Comments 3 Likes
The data science ecosystem: R vs Python vs Substitutes
Posted on November 9, 2016 at 1:30am 0 Comments 7 Likes
The data science ecosystem: R vs Python vs Substitutes
In this post, I show a network analysis of the R and Python ecosystems in terms of their competitors. The objective of the post is to -
- Identify the key tools/languages being commonly searched in the data science area related to R/Python
- Identify the sets of associated tools
To identify the typical substitutes/ competitors of a tool, I use the Google search autofill recommendations.…
ContinueImplementing data science projects – the five essential skill sets
Posted on March 17, 2016 at 11:30pm 0 Comments 10 Likes
The future of business, it is argued, is digital. At the core of this digital transformation is the ability to harness data in enabling better business decisions. Typically, organizations have teams of experts who work on existing data sets to apply diverse analytic tools and techniques to make sense of the data. The more statistically advanced among these teams work on typical ‘data science’ problems. Data science problems are where you need to apply sophisticated algorithms on large data…
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