What is Data Science, how is it used?
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Preregistration For Data Science? - Neuroskeptic | DiscoverMagazine.com

Preregistration For Data Science? - Neuroskeptic | DiscoverMagazine.com | What is Data Science, how is it used? | Scoop.it
In a post on the issue of preregistration in science, statistician and political scientist Andrew Gelman writes (my emphasis) that: I support proposals in
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In the worst case scenario, everyone would cheat in this way, and only results that are liked would see the light of day.

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What is Data Science, how is it used?
Can I use data science to make a difference in my company (HECK YES)
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Data Science is real » Great Lists to Follow

Data Science is real » Great Lists to Follow | What is Data Science, how is it used? | Scoop.it
Carla Gentry CSPO's insight:

There are some great lists out there to follow for Data Science and Technology – Check out a few I have been honored to be listed on – Please feel free to check out everyone on these lists, some really great folks out there!

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» Advisor 4.04

» Advisor 4.04 | What is Data Science, how is it used? | Scoop.it
We use predictive analytics to reduce employee attrition & increase performance for high volume roles like Call Centers, Insurance Agents, Sales Reps, Tellers, Sales Engineers, Personal Bankers and the like.
Carla Gentry CSPO's insight:
Who Uses Advisor™? Over 800 customers, in a myriad of industries use Advisor today. HR, recruiters and hiring managers use Advisor on a day to day basis for smarter hiring decisions. Analytics professionals upload their predictive models into Advisor – so workforce leaders can make use of their models. HRIS, HCM, ATS, PEOs and other workforce systems connect to Advisor’s predictions to enhance their value
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Data Science

DJ Patil, Former U.S. Data Scientist & Roxanne Varza, DIrector, Station F and Loic Le Meur, Founder & CEO, Leade.rs
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Data Science - DJ Patil, Former U.S. Data Scientist https://youtu.be/fzGzKUsJB3U via @YouTube
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Data Science is real » Big Data needs Data Science but Data Science doesn’t need Big Data

Data Science is real » Big Data needs Data Science but Data Science doesn’t need Big Data | What is Data Science, how is it used? | Scoop.it
Carla Gentry CSPO's insight:
Data science has been around for decades, and it’s not just big data. I hear a lot of people clumping these two together like they go hand-in-hand, which I agree with to an extent. However, big data needs data science but data science doesn’t necessarily need big data.
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4 Women Leading the Way in Business Intelligence

4 Women Leading the Way in Business Intelligence | What is Data Science, how is it used? | Scoop.it
To find out what it takes to become a successful female executive within BI, we interviewed four female professionals at the top of the field. Here are their stories.
Carla Gentry CSPO's insight:
It’s no secret that there’s a disproportionately low number of women in STEM (science, technology, engineering, mathematics) fields.
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Data Science is real » Proud to be part of 25 Most Influential #WomenLeaders

Data Science is real » Proud to be part of 25 Most Influential #WomenLeaders | What is Data Science, how is it used? | Scoop.it
Carla Gentry CSPO's insight:
“The past two decades have seen a huge surge of women taking on key roles in the world of emerging technology. When we decided to put together this list, we were thrilled to discover dozens of outstanding candidates, and we have picked the top 25 female thought-leaders, champions, and innovators in the field.”
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Do Data Scientists Still Really Exist?

Do Data Scientists Still Really Exist? | What is Data Science, how is it used? | Scoop.it
It’s a question that’s asked a lot lately, and the truth is, data scientists not only exist -- one of them may become president someday. That is a bold sta
Carla Gentry CSPO's insight:
Well hell yes WE exist, what do you think I do all day, twittle my fingers lol
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DrDids's curator insight, March 17, 8:10 AM
Looking at the stars from the Earth of vice versa? but where is the data gutter? Oscar  V-Wilde
 
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It Seems Like Anyone Can Be a Data Scientist... but Is It True?

It Seems Like Anyone Can Be a Data Scientist... but Is It True? | What is Data Science, how is it used? | Scoop.it

This leads me to believe that the real question here is, “Can anyone BE a data scientist?” And to that I would say no, not at all, for the very reasons I just mentioned. In my experience, not even your top CS or STEM majors from a top school can easily become good data scientists, without additional training in it, and some personal factors. Apart from its multidisciplinary nature, data science requires a deep love of the divergence between observed reality in data and the prediction of mathematical models. To do that, one needs something more than just a mastery of tools. One needs a love for imperfection.


Carla Gentry CSPO's insight:
But that brings me back, full circle, to the confusion surrounding one being able to “call” one’s self a data scientist, even if one doesn’t possess the entire toolkit, the experience and the love of imperfection and variability. As a budding profession, data science has a lot of work to do. We need a more standardised multidisciplinary curriculum, implemented by people with field and business experience (not just academics) and perhaps a professional body or two that can guard the gates.
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Carla Gentry CSPO's curator insight, March 4, 7:42 AM
I’ve been in this field almost 20 years, from back before the term “data science” existed, so I’ve seen many things. In fact I believe data science excellence requires a number of years in actually applying it before one can truly understand data, how it behaves, how different models work, backwards and forwards, etc. Yet, most importantly, excellence requires making mistakes and understanding mistakes, along with appreciating the variations between observed and predicted reality. Thus, I affectionately call data science the science for imperfect people, like myself.
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» What if HR Was Paid to Reduce Employee Turnover?

» What if HR Was Paid to Reduce Employee Turnover? | What is Data Science, how is it used? | Scoop.it
We use predictive analytics to reduce employee attrition & increase performance for high volume roles like Call Centers, Insurance Agents, Sales Reps, Tellers, Sales Engineers, Personal Bankers and the like.
Carla Gentry CSPO's insight:
What if this changed? What if HR was paid not only to hire quickly but to also be responsible for reducing turnover in roles that have a lot of volume? What would need to change to make this happen? How would this affect day to day operations?
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The one critical skill many data scientists are missing

The one critical skill many data scientists are missing | What is Data Science, how is it used? | Scoop.it
Data science is a new career for the age of Big Data (whatever that means this week), but you can see that it’s at the intersection of qualities many people have been developing for years. As a graduate of the Science to Data Science (S2DS) summer school, I know people who have come to data science from a wide variety of backgrounds and found a new niche for themselves.
Carla Gentry CSPO's insight:
When I started to learn about data science and consider it as a career choice, there was a diagram that I came across regularly and still come across today, in articles and even text books aimed at introducing and educating the world about the “sexiest job of the 21st century.” First created by Drew Conway, it illustrates the three broad skill groups you need to be a data scientist.
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Employee Life Time Value and Cost Modeling - Predictive Analytics Times - predictive analytics & data science news

Employee Life Time Value and Cost Modeling - Predictive Analytics Times - predictive analytics & data science news | What is Data Science, how is it used? | Scoop.it
Understanding the Most Expensive Asset Practically every business shares the same biggest cost – employees. This makes sense – even in this age of robots and computers, human talent is behind everything that a company does. People are the source of innovation, growth, and competitive edge for every company. Given this importance, it’s a bit …
Carla Gentry CSPO's insight:
We address employee cost, performance, attrition and lifetime value to bring the practice of Human Resources into the information age. Only with these metrics will the actual value and dynamics of our "Human Resources" be known.
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» How Do Algorithms Reduce Bias During the Talent Acquisition Process?

» How Do Algorithms Reduce Bias During the Talent Acquisition Process? | What is Data Science, how is it used? | Scoop.it
First we need to remember that the hiring process is a process of discrimination – though not in the way we normally think of discrimination. The single goal during the interview process is to discriminate between someone who can do the job vs. someone who can’t.  We should only be paying attention to fulfilling this mandate for our companies.The problem is that we are human and we can’t avoid many other distracting factors even if we try desperately to remind ourselves.Unless they’ve been told otherwise, algorithms don’t care about gender or color or disability. Algorithms are focused on finding candidates that are proven to deliver performance for the company (which is the only reason to hire an employee anyway)
Carla Gentry CSPO's insight:
So – one way analytics can help to humanize the process is to scrub bias, be transparent and remove mystery factors from the interview process.
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Data science is creating a tidal wave of opportunity for women to get into executive leadership

Data science is creating a tidal wave of opportunity for women to get into executive leadership | What is Data Science, how is it used? | Scoop.it
Women now make up 40 percent of graduates with degrees in statistics — that’s a good indicator for women in an environment increasingly obsessed with data. As we’ve seen with most technologies, the code is eventually abstracted away from the user and the dirty work of putting the tech to use in real business situations begins. Women no longer need to be expert coders to get in on the data science game.
Carla Gentry CSPO's insight:
Women now make up 40 percent of graduates with degrees in statistics — that’s a good indicator for women in an environment increasingly obsessed with data. As we’ve seen with most technologies, the code is eventually abstracted away from the user and the dirty work of putting the tech to use in real business situations begins. Women no longer need to be expert coders to get in on the data science game.
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Black Duck Software's curator insight, February 6, 10:35 AM
Interesting developments in #datascience here for women in executive leadership.
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» Five Ways to Select a High Value Predictive HR Project

» Five Ways to Select a High Value Predictive HR Project | What is Data Science, how is it used? | Scoop.it
We use predictive analytics to reduce employee attrition & increase performance for high volume roles like Call Centers, Insurance Agents, Sales Reps, Tellers, Sales Engineers, Personal Bankers and the like.
Carla Gentry CSPO's insight:
Greta Roberts, CEO Talent Analytics, Corp. 1. Identify a business problem to solve. Almost everyone working on modern predictive analytics discusses the need for a defined business problem before engaging in a predictive project. And yet, the #1 question I get in speaking with businesses is “I need to do a predictive project, bu
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Partnering with data to create insightful stories

Partnering with data to create insightful stories | What is Data Science, how is it used? | Scoop.it

One of the reasons for that is similar to the well-known phenomenon called mathematical anxiety, where people are afraid of maths as a result of past difficulties and traumas. Every one of us have interacted with data analyses (at work, newspapers or academic research) that were created by unskilful communicators, people that might be amazing statisticians but lack the ability to convey the stories behind the numbers. That creates anxiety and could prevent professionals from even trying to understand data.

Carla Gentry CSPO's insight:
Data is no longer "next year's big thing", we have gone through that many times over and almost everyone accepts data as a valuable team member. But not everyone can understand and make use of it optimally, which means lots of decisions are still made based on intuition - if you don't believe me, check PwC's Global Data and Analytics Survey 2016, it shows some interesting numbers on how often managers use data during the decision-making process. Data education is a crooked road and we have a long journey ahead of us.
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20 Cheat Sheets: Python, ML, Data Science, R, and More

20 Cheat Sheets: Python, ML, Data Science, R, and More | What is Data Science, how is it used? | Scoop.it
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, e…
Carla Gentry CSPO's insight:
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, correlation, outliers, regression Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, time series, cross-validation, model fitting, dataviz, and many more. To keep receiving these articles, sign up on DSC. Previous entries are listed below the picture.
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Data Science is real » You don’t know how to hire a REAL Data Scientist!

Data Science is real » You don’t know how to hire a REAL Data Scientist! | What is Data Science, how is it used? | Scoop.it
Carla Gentry CSPO's insight:
I was recently contacted by a recruiter concerning a Director of Analytics position at a Private University in my home state; they wanted to know if I could recommend someone for the position since I had a background in Education and Data Science
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Data Science is real » Honored to be a Women In Data

Data Science is real » Honored to be a Women In Data | What is Data Science, how is it used? | Scoop.it
Women in Data
Carla Gentry CSPO's insight:
So, for the 1st time in my life, I am a “cover girl” thanks to O’Reilly – I have received many congrats and “hat’s off” comments, to them I say “Thank You” :o)
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Three predictive modeling flaws that cripple data science projects

Three predictive modeling flaws that cripple data science projects | What is Data Science, how is it used? | Scoop.it
Before you kick off new data science projects, read about these three common pitfalls that can trip up data scientists.
Carla Gentry CSPO's insight:
Data science projects can provide immense business value by guiding companies toward increased revenue or improved operations, but can also be damaging if done wrong. (EXPERIENCE does matter!!!)
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Celebrating Women's Day: 33 Women in Data Science from around the World & AV Community

Celebrating Women's Day: 33 Women in Data Science from around the World & AV Community | What is Data Science, how is it used? | Scoop.it
This article features 33 women from data science, machine learning & analytics.Here we have women leaders from Google, Linkedin,MapR,Stanford
Carla Gentry CSPO's insight:
I am so honored to be included with such WONDERFUL women in tech #WIT
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Carla Gentry CSPO's curator insight, March 8, 10:20 AM
#10 SO HONORED!  Carla Gentry is a Data Scientist at Talent Analytics, Corps. She carries an invaluable experience of over 20 years which includes working for Fortune 500 companies like Hershey, Kraft, Johnson & Johnson, Kellogg’s and Firestone. She is one of the most popular personalities in Big Data community to follow on Twitter.
Carla Gentry CSPO's curator insight, March 8, 10:22 AM
WOW, what an HONOR! I am so thrilled to be mentioned with such terrific ladies in tech and science #STEM! 
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» 3 Parallels Between the Future of Retail and the Future of the Workforce

» 3 Parallels Between the Future of Retail and the Future of the Workforce | What is Data Science, how is it used? | Scoop.it
We use predictive analytics to reduce employee attrition & increase performance for high volume roles like Call Centers, Insurance Agents, Sales Reps, Tellers, Sales Engineers, Personal Bankers and the like.
Carla Gentry CSPO's insight:
I loved this recent article from the CEO of Walmart about his 3 Predictions for the Future of Retail. I saw so many parallels to the future to the workforce and the future of work – I wanted to share them.
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Using AI to reduce bias in hiring | Ifeoma Ajunwa, The University of the District of Columbia

Learn how you can use data and science to make work better at https://g.co/rework Ifeoma Ajunwa, assistant professor at The University of the District o

Via David Green
Carla Gentry CSPO's insight:
Learn how you can use data and science to make work bette
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Talent Socio's curator insight, February 28, 11:40 PM
Technology implications are going to be there in every space. Recruitment has immense potential for technology interventions.
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How Predictive Technology is Changing Advertising

How Predictive Technology is Changing Advertising | What is Data Science, how is it used? | Scoop.it
Advertisers have done everything they can to find out more about their audience so they can make their ads more effective. They have used online technology like cookies to try to predict what audience members will want, such as by looking at what other websites they have visited.
Carla Gentry CSPO's insight:
Advertisers have done everything they can to find out more about their audience so they can make their ads more effective. They have used online technology like cookies to try to predict what audience members will want, such as by looking at what other websites they have visited. Read more at http://www.business2community.com/marketing/predictive-technology-changing-advertising-01773066#3ZWFEBvFpxoUW7EP.99
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» Are All Predictive Talent Acquisition Platforms Created Equally?

» Are All Predictive Talent Acquisition Platforms Created Equally? | What is Data Science, how is it used? | Scoop.it
We use predictive analytics to reduce employee attrition & increase performance for high volume roles like Call Centers, Insurance Agents, Sales Reps, Tellers, Sales Engineers, Personal Bankers and the like.
Carla Gentry CSPO's insight:
Detailed predictions require a level of interaction with your company’s data (HR data plus Line of Business Data) to determine what attributes predict a top performer for your company vs. another company. These attributes can be very different company and by company.
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Managing Big Data’s Big Risks

Managing Big Data’s Big Risks | What is Data Science, how is it used? | Scoop.it
The good news is that the hazards of Big Data can be largely avoided. But they won’t be unless we zealously protect people’s privacy, detect and correct unfairness, use algorithmic recommendations prudently, and maintain a rigorous understanding of algorithms’ inner workings and the data that informs their decisions.
Carla Gentry CSPO's insight:
The good news is that the hazards of Big Data can be largely avoided. But they won’t be unless we zealously protect people’s privacy, detect and correct unfairness, use algorithmic recommendations prudently, and maintain a rigorous understanding of algorithms’ inner workings and the data that informs their decisions.
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» The Beginner’s Guide to Predictive Workforce Analytics

» The Beginner’s Guide to Predictive Workforce Analytics | What is Data Science, how is it used? | Scoop.it
We use predictive analytics to reduce employee attrition & increase performance for high volume roles like Call Centers, Insurance Agents, Sales Reps, Tellers, Sales Engineers, Personal Bankers and the like.
Carla Gentry CSPO's insight:
Human Resources Feels Pressure to Begin Using Predictive Analytics
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