Principal Data Scientist, Inventory Placement - Toronto, Canada - Amazon Development Centre Canada ULC

Amazon Development Centre Canada ULC

Verified Company

Toronto, Canada

2 weeks ago

Posted by:

Sophia Lee

beBee Recruiter

Description

MS in Mathematics, Statistics, Machine Learning, or a related quantitative field

7+ years industry experience building successful production software systems
Deep understanding and practical experience in statistics and machine learning, with a focus on experimental design and causal inference.

The Inventory Placement team within the Supply Chain Optimization Technologies organization seeks a Principal Data Scientist to lead the design and implementation of experiments and causal impact analyses across all placement initiatives.

Key job responsibilities

To be successful in this role, you must be able to turn ambiguous business questions into clearly defined problems, develop quantifiable metrics and deliver results that meet high scientific standards.

About the team

The Supply Chain Optimization Technologies (SCOT) organization owns Amazon's global inventory management systems: we decide what, when, where, and how much we should buy to meet Amazon's business goals and to make our customers happy.

We do this for millions of items, for hundreds of product lines worth billions of dollars of inventory world-wide.

Our systems are built entirely in-house, and are on the cutting edge in automated large-scale business, inventory and supply chain planning and optimization systems.

We foster new game-changing ideas, creating ever more intelligent and self-learning systems to maximize the efficiency of Amazon's inventory investment and placement decisions.

The Placement team operates within Amazon's Supply Chain Optimization Technology/Inventory Planning and Control organization.

Its primary responsibility is strategically determining the placement of every inventory unit for both the Retail and FBA businesses across all Amazon websites globally.

The team manages systems that optimize the vast fulfillment network, ensuring the ideal inventory placement to enhance customer and seller satisfaction on a global scale.

Toronto, ON, CAN

PhD in Mathematics, Statistics, Machine Learning, or a related quantitative field
Experience working in data science in the supply chain domain
Significant peer reviewed scientific contributions in Data Science, Analytics, Statistics, or related field.
Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations
Functional knowledge of AWS platforms such as S3, Glue, Athena, Sagemaker.
Excellent written and verbal communication skills. The role requires effective communication with colleagues from computer science, operations research and business backgrounds
Successful record of developing less experienced team members to a successful career track.

Amazon is committed to a diverse and inclusive workplace.

Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, disability, age, or other legally protected status.

If you would like to request an accommodation, please notify your Recruiter.