RSS Featured Blog Posts
  • Poker, Probability, Monte Carlo, and R
    My daughter just started a business analytics Master's program. For the probability sequence of the core statistics course, one of her assignments is to calculate the probability of single …
    steve miller
  • What a CEO needs to know about Machine Learning algorithms
    During my first project in McKinsey in 2011, I served the CEO of a bank regarding his small business strategy. I wanted to run a linear regression on the bank's data but my boss told me: "Don't do it. They don't understand statistics". (We did not use Machine…
    Pedro URIA RECIO
  • Are You Ready To Become A Chief Data Scientist?
    You know who you are. A high-calibre machine learning magician, a well-versed wrangler of data... but you want a bit more from your role. That may be progression, more money or the chance to work on new, more exciting projects, but where do you go from here?   Many companies are looking to increase investment […]
    Matt Reaney
  • Artificial Intelligence (AI) in Retail Market to hit $8bn by 2024
    Artificial Intelligence (AI) in Retail Market size is set to exceed USD 8 billion by 2024; according to a new research report by Global Market Insights, Inc.  The AI in retail market is driven by the increasing investments in it across the globe. The growing investment in the technology is attributed to the wide applications […]
    Sagar
  • Summarize and explore the data using SmartEDA
    Created an R package for exploratory data analysis. Package name is SmartEDA now available on CRAN. This package includes multiple custom functions to perform initial exploratory analysis on any input data describing the structure and the relationships present in the data. The generated output can be obtained in both summary and graphical form. The graphical form […]
    Dayanand

Data Scientist Interviews

What data scientist’s do all day at work

Ram Narasimhan of GE talks about the importance of curiosity and what makes his day

“What I do as a Data Scientist” Dan Mallinger

Excerpt from Data Scientist Interviews “I’m a data scientist with degrees in mathematical sciences and organizational psychology; I also have significant academic training in computer science and sociology. I’ve spent my career in statistics, analytics, and technology roles but almost entirely under business groups, which has framed much of my professional outlook. Today, I am the Director of Data Science for Think Big and have been with the company for four years.”

Interview: Michael Brodie – We Can’t Rely on Machines

Excerpt from Data Scientist Interviews “So yes, there is a lot of hype?But I actually think it is far more profound and powerful than most people are conceiving it at the moment. It has already changed a very large number of operating processes in health care, manufacturing, marketing and stock markets. How-ever, it is not as widely used as one might think. Big Data and Big Data Analytics are in their infancy with respect to operational deployment and our understanding of it.”

Crushed it! Landing a data science job by Erin Shellman

“Data science interviews are the worst because data science is interdisciplinary: code for “you have to know everything about all the disciplines.”  Depending on the company and the team, your interview might look like a software developer’s interview, or it might look a like a statistician’s interview, and the bad news is that virtually none of the material overlaps.  I recently spent a ton of time studying for interviews and I’ve got some hot tips to pass along if you’re thinking about a move soon.”

 

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