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Tim Matteson liked Ram Alagianambi's blog post 5 common causes of friction between data scientists and the rest of the stakeholders

Jul 27

Ram Alagianambi's blog post was featured

5 common causes of friction between data scientists and the rest of the stakeholders

Overview:As a data scientist, have you ever been frustrated that your stakeholders don’t see the value that you bring to the table? You may ask yourself, “How far should I go in explaining the work I do or what my models are doing?” If that sounds like you, then pay close attention to this post and the next, as they are all about improving collaboration between data scientists and other stakeholders. This is a two-part post: This article covers underlying assumptions and gaps in understanding…See More

Jul 26

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Ram Alagianambi's blog post was featured

5 meaningful ways to improve the adoption of data science in your organization

Overview:This post is about improving the effectiveness of the data science team and improving collaboration between data scientists and stakeholders for better outcomes. Aligning goals:Regardless of the specific project, agreeing on the expected outcomes and goals before beginning the work is a best practice. But with the advent of machine learning (ML) models, it’s for both sides to discuss the critical measures of success for the given project. Using a framework such as the Objective Key…See More

Jul 23

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Jul 17

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Company:: LendingClub

Job Title:: Head of Product, Membership

Seniority:: Director

Job Function:: Solutions Architect

Number of employees:: 1.000 to 4.999

Industry:: Financial/Banking

Interests:: Contributing, New venture

Ram Alagianambi's Blog

5 meaningful ways to improve the adoption of data science in your organization

Posted on July 20, 2020 at 9:00pm 0 Comments 0 Likes

Overview:

This post is about improving the effectiveness of the data science team and improving collaboration between data scientists and stakeholders for better outcomes.

Aligning goals:

Regardless of the specific project, agreeing on the expected outcomes and goals before beginning the work is a best practice. But with the advent of machine learning (ML) models, it’s for both sides to discuss the critical measures of success for the…

Continue

5 common causes of friction between data scientists and the rest of the stakeholders

Posted on July 20, 2020 at 8:30pm 0 Comments 1 Like

Overview:

As a data scientist, have you ever been frustrated that your stakeholders don’t see the value that you bring to the table? You may ask yourself, “How far should I go in explaining the work I do or what my models are doing?” If that sounds like you, then pay close attention to this post and the next, as they are all about improving collaboration between data scientists and other stakeholders.

This is a two-part post: This article…

Continue