[slideshare id=61486991&doc=whereshouldyouputyourdatascientists-160429025555]
Data Science: Ranking Online Influencers
Data science is the defining specialty of the business of big data and an emerging career path for those who love to find new insights in the gazillion bytes of data created each day. It’s where you find fierce competition for talent, the jobs of the future, new training programs and courses, new ventures, and new products. But where to find the data science-relevant online conversations with the most impact? Continue reading
DJ Patil at LeWeb, December 2012
[youtube http://www.youtube.com/watch?v=J_CYKk8q1Ao]
Summary of the presentation by Ben Rooney here
Update: Ben Rooney interviews DJ Patil
[youtube http://www.youtube.com/watch?v=0LtzMhr0ZCM]
Data Science at Zillow (Slideshare)
[slideshare id=45132578&doc=pythondatascienceatzillow-150225104833-conversion-gate02]
Vincent Granville’s 66 job interview questions for data scientists
- What is the biggest data set that you processed, and how did you process it, what were the results?
- Tell me two success stories about your analytic or computer science projects? How was lift (or success) measured?
- What is: lift, KPI, robustness, model fitting, design of experiments, 80/20 rule?
- What is: collaborative filtering, n-grams, map reduce, cosine distance?
- How to optimize a web crawler to run much faster, extract better information, and better summarize data to produce cleaner databases?
- How would you come up with a solution to identify plagiarism?
- How to detect individual paid accounts shared by multiple users?
- Should click data be handled in real time? Why? In which contexts?
- What is better: good data or good models? And how do you define “good”? Is there a universal good model? Are there any models that are definitely not so good?
- What is probabilistic merging (AKA fuzzy merging)? Is it easier to handle with SQL or other languages? Which languages would you choose for semi-structured text data reconciliation?
To see the other 56 questions assessing “the technical horizontal knowledge of a senior candidate at a high level” go here
Survey: The Hunt for Unicorn Data Scientists Boosts the Salaries of Predictive Analytics Professionals
Unicorn Data Scientists (upgraded from “sexy data scientists”) are hard to find and are paid more than $200,000 per year. A new survey finds that the rising data science tide lifts the compensation of all other data analytics professionals, even if they don’t know how to code.
The Burtch Works Study: Salaries for Predictive Analytics Professionals is based on interviews with 1,757 data analytics professionals conducted over the 12 months ending April 2015 by executive recruiting firm Burtch Works. It is a unique source of information in that it does not rely on self-reporting or data provided by human resources departments. It also provides insights into how the demand for data scientists impact the salaries of other data analytics professionals because it excludes data scientists, covered in a separate Burtch Works study, published earlier this year (I wrote about that study here).
Burtch Works defines predictive analytics professionals as those who can “apply sophisticated quantitative skills to data describing transactions, interactions, or other behaviors of people to derive insights and prescribe actions.” Data scientists are a subset of this group—they have the “computer science skills necessary to acquire and clean or transform unstructured or continuously streaming data, regardless of its format, size, or source.”
The additional computer science skills put data scientists on top in terms of compensation regardless of their levels of experience and managerial responsibilities but predictive analytics professionals are keeping up, seeing their salaries and bonuses rise. For example, the median base salary for the most experienced individual contributors rose from $115,250 last year to $125,000 this year and for managers managing teams of ten or more the median base salary rose from $225,000 to $235,000.
Predictive analytics professionals continue to benefit from the increasing demand and short supply for their quantitative analysis skills. The median base salary of individual contributors varies from $76,000 for those at level 1 (0 to 3 years of experience) to $125,000 for those at level 3 (9+ years of experience). The median bonus received varies from $8,100 to $18,100, depending on job level.
The median base salary of managers varies from $125,500 for those at level 1 (1 to 3 reports) to $235,000 for those at level 3 (10+ reports). The median bonus received by managers varies from $23,000 to $75,000 depending on job level.
More and more people are attracted by the demand for data analytics professionals and the potential to become a unicorn. Data recently released by the National Center for Education Statistics, according to Phys.org, shows bachelor’s degrees in statistics grew 17% from 2013 to 2014. This marks 15 consecutive years the number of undergraduates in statistics has risen, increasing by more than 300% since the 1990s. In addition, from 2000 to 2014, master’s and doctorate degrees in statistics also grew significantly at 260% and 132%, respectively.
“The Bureau of Labor Statistics projects job growth for statisticians will increase 27% between 2012 and 2022, outpacing the projected 11% rate for all other occupations. The number of graduates in statistics each year—approximately 2,000 bachelor’s degrees, 3,000 master’s degrees and 575 doctorate degrees—seems unlikely to match this demand,” says Phys.org.
Originally published on Forbes.com
Tom Davenport on Managing Data Scientists (Video)
[youtube https://www.youtube.com/watch?v=VK4-ASEUmgE?rel=0]




