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Tina Lakinger

Tina Lakinger

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Principal, Technical Product Management @ Amazon Fulfillment Technologies & Robotics Principal Technical Product Lead, Mobility at Amazon Robotics
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Education

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Northwestern University

Master of Science (M.S.), Data Science (formerly Predictive Analytics) 2013-01-01 - 2015-01-01
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Penn State University

Graduate Certificate, Applied Statistics 2011-01-01 - 2012-01-01
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Excelsior University

BS, Liberal Studies 2009-01-01 - 2010-01-01
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University of Chicago Laboratory Schools

High School, -

Work Experience

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Amazon Fulfillment Technologies & Robotics

Current

Amazon Fulfillment Technologies & Robotics

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Amazon

2014-04-01 - 2015-10-01

Amazon

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Sanofi

2012-03-01 - 2014-04-01

Sanofi

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LTI (Logic Technology Inc.)

2010-03-01 - 2012-03-01

LTI (Logic Technology Inc.)

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Granite Services, Inc.

2008-11-01 - 2009-11-01

Granite Services, Inc.

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Professional Insurance Agents

2007-11-01 - 2008-10-01

Professional Insurance Agents

Skills

Consensus Building Business Requirements Strategic Initiatives Team Culture Communication Product Strategy Data Mining Matrix Management Data Analysis Business Process Business Metrics Performance Metrics Root Cause Analysis Ad Hoc Reporting SQL R Statistics Statistical Modeling Microsoft Office MS Project

Summary

I’m the technical product leader for Mobility across Amazon Robotics. The AR system is a non-deterministic, massively parallel processor of “stuff”; the many robots on a floor are only the most visible portion of everything that goes on to orchestrate the dance. I own the full stack that prioritizes, allocates, and executes any time we need to move something from A to B in the AR system, from the physical hardware on the floor, to the on-device firmware, to the on-prem and cloud software. My blue and orange ‘bots operate 24/7/365/10 across four continents. I earn trust across Amazon’s logistics businesses by delivering results not only with the “right now” solution, but with a roadmap towards the long-term correct solution. I build coalitions of teams with diverse priorities, finding the middle path between analysis paralysis and priority churn, and lead them through technical and business ambiguity.

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