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  1. Home
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  3. Talia Borodin
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Talia Borodin

Founder
Founder
Amaro Science
Country or state 
Canada (Ontario)
Available to 
Global
City 
Toronto
Fee 
Ask for pricing
Languages 
English
Volunteer
Yes

Personal Details

Bio

Talia Borodin has been advising companies and not for profits in her capacity as founder of Amaro Science for the past 3.5 years. She holds an MSc in Mathematics from Queen’s University and has worked in Data Science and Predictive Analytics for the past 15 years. Ms. Borodin has worked in fraud detection, politics, eCommerce, finance, healthcare and more. She is credited with creating some of the first ever national micro-targeting models used in progressive politics before moving home to her native Canada to build the first Data Science team at a global e-commerce company.

Current position (1)

Founder

Amaro Science

Degrees (2)
Masters of Science
Queen's University
2002 to 2003
Bachelor of Science
Queen's University
1998 to 2002

Presentations

Presentations (2)
Introduction to Data Mining

An introductions to data mining and predictive analytics tailored to your particular industry. Past presentations have focussed on e-commerce, political organizing and fraud detection with more custom topics available by request. This presentation will cover basic definitions and concepts through interactive model creation as well as audience participation and Q & A.

Designing for Data

This presentation was given to students studying art and technology at Shenkar engineering and design in Tel Aviv. It covers many popular topics relevant to the art of design such as AB testing, machine learning art transformations and data visualization.

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Books & Articles (1)

Think your company needs a Data Scientist? You're probably wrong.

Expertise (12)

Science
Social & Political
Technology
Data Science Advanced Analytics Data Mining A/B testing Business Intelligence Analytics Statistics Mathematics Mathematical Modeling
Recommendations
Why choose me? 

I make data fun and interesting with my no nonsense attitude towards demystifying data.

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