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2016-09-27T00:00:00.000Z

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Pasha Roberts

Chief Scientist

Talent Analytics Corp

Direct Phone: (617) ***-**** ext. ***       

Email: p***@***.com

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Talent Analytics Corp

One Mifflin Place Suite 400

Cambridge, Massachusetts 02138

United States

Company Description

Talent Analytics, Corp. is the leader in predicting employee performance. Its award winning Talent Analytics Advisor™ platform quickly measures employee aptitude (innate talent), delivering 11 numbers per person. Aptitude scores are included in predictive ... more

Find other employees at this company (16)

Background Information

Employment History

Chief Software Architect

Target Teams Inc

Affiliations

Teams Advisor
Target Corporation

Founder
Lineplot Productions LLC

Founder
WebLine Communications Corporation

Education

Master of Science Degree

Financial Engineering

MIT Sloan School of Management

bachelors degree

Economics and Russian Studies

The College of William and Mary

dual Bachelors degree

Economics and Russian Studies

The College of William and Mary

Web References (181 Total References)


MIT Sloan Boston Alumni Association - Big Data and Workforce Analytics

www.mitsloanboston.com [cached]

Description: Pasha Roberts, Co-Founder & Chief Scientist at Talent Analytics, is on his second successful startup venture, having co-founded and sold Webline Communications for $325 million in 1999. He wrote the first implementation of the software over a decade ago, and today he continues to drive new features and platforms for the company.

Pasha holds a bachelors degree in Economics and Russian Studies from The College of William and Mary, and a Masters of Science degree in Financial Engineering from the MIT Sloan School of Management.
Join Pasha for a discussion on how he is building his startup to pursue the Workforce Analytics market using Big Data.


Predictive Analytics Times - predictive analytics & big data news

www.predictiveanalyticsworld.com [cached]

Wise Practitioner - Predictive Workforce Analytics Interview Series: Pasha Roberts at Talent Analytics, Corp.

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Wise Practitioner - Workforce Predictive Analytics Interview Series: Pasha Roberts at Talent Analytics
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Presented by: Pasha Roberts, Chief Scientist, Talent Analytics, Corp....
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Pasha Roberts, Chief Scientist, Talent Analytics, Corp.


Wise Practitioner - Predictive Workforce ...

www.predictiveanalyticsworld.com [cached]

Wise Practitioner - Predictive Workforce Analytics Interview Series: Pasha Roberts at Talent Analytics, Corp.

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Wise Practitioner - Workforce Predictive Analytics Interview Series: Pasha Roberts at Talent Analytics
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Presented by: Pasha Roberts, Chief Scientist, Talent Analytics,...


risk management

data-informed.com [cached]

Talent Analytics Corp. co-founder and Chief Scientist Pasha Roberts discusses how predictive analytics can improve recruiting, KPI performance, and the flow of talent through the organization. Read More...


Editor's Note: Pasha Roberts ...

data-informed.com [cached]

Editor's Note: Pasha Roberts will present Predictive Job Maps - Modeling an Entire Workforce with a Tree of Models at the Predictive Analytics World Conference, taking place April 3-7 in San Francisco.

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Pasha Roberts, co-founder and Chief Scientist at Talent Analytics Corp., fielded questions from Data Informed about how organizations can apply predictive analytics to map these movements and determine which types of employees are most likely to change roles, which roles best suit individual employees, and how this knowledge can improve hiring and employee performance.
Data Informed: What kinds of data make up a predictive job map?
Pasha Roberts: Each node in the map is a role, for example, "Underwriter I" or "Inside Sales Representative. Then, we map the traffic between each role: hires, promotions, demotions, transfers, terminations, and actual performance in the role. This gives us a set of history and probabilities for how people really move and perform through the organization, which is not always how HR has planned it. This emergent order usually brings a lot of insight, but it is nothing new. People have been doing this with Markov chains for a long time.
Pasha Roberts, Co-Founder and Chief Scientist, Talent Analytics Corp.
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Pasha Roberts, Co-Founder and Chief Scientist, Talent Analytics Corp.
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Roberts: Two kinds of decisions come from this map: macro and micro.
At the micro level, we can identify attractive paths for candidates or employees through an organization, years before the person has developed the skills or experience to take the later roles. An attractive path is defined as a role in which they have a high probability of being successful in the role: If a candidate applied for a customer support role but the models find he would be more likely to stay and to produce more value as an inside sales rep, we can put the candidate there instead.
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Roberts: At the employee level, a map of models will make smarter choices for the entire organization. For example:
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Roberts: The micro and macro components of the map work together.
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Roberts: It is useful for both.
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Roberts: Within a general flight risk number, we strive to understand types of termination: Is it because the employee wants bigger things, more money, or because they can't do the job?
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Roberts: Just knowing a potential path for someone doesn't do much for anyone.
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Roberts: This isn't physics, this is people.
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Editor's Note: Pasha Roberts will present Predictive Job Maps - Modeling an Entire Workforce with a Tree of Models at the Predictive Analytics World Conference, taking place April 3-7 in San Francisco.

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