Lead Data Scientist for UTR Optimization

3 weeks ago


Toronto, Ontario, Canada Amazon Canada Fulfillment Services, ULC Full time

Are you ready to take on a pivotal role? Amazon Canada Fulfillment Services, ULC is seeking a talented and driven Data Scientist to enhance our North America Sort Centers (NASC) Engineering Data, Product, and Simulation Team.

The Sort Center network serves as a vital Middle-Mile solution within the Amazon Transportation Services (ATS) division, connecting Fulfillment Centers to the Last Mile. Our customers' experiences hinge on our capability to effectively manage volume flow throughout this network.

Key Responsibilities:
The Data Scientist will be responsible for designing and executing solutions to tackle intricate business challenges through simulation. In this capacity, you will utilize advanced analytical techniques and statistical methodologies to extract insights from extensive datasets, while also developing intuitive simulations and data visualizations.

Your contributions will span all layers of a data solution, collaborating closely with process design engineers, business intelligence engineers, and technical product managers to gather relevant datasets, construct simulation models, and present key findings to business leaders and stakeholders. Your work will reflect a harmonious blend of scientific rigor and business relevance.

As a member of this team, your impact will resonate throughout the entire NASC organization, providing ample opportunities for professional growth and learning within the NASC Engineering team.

This position will establish you as the primary simulation expert, granting you a unique opportunity to shape and advance simulation best practices within our team.

To excel in this role, you should be adept at:
- Transforming ambiguous business inquiries into clearly defined problems.
- Developing measurable metrics and delivering results that adhere to high standards of data quality, security, and privacy.

About the Team:
The NASC Engineering's Product and Analytics Team is dedicated to creating tools for in-house simulation and optimization, catering to the needs of our internal and external stakeholders, including Process Design Engineering, NASC Engineering, ACES, Finance, Safety, and Operations.

We specialize in developing data science tools to assess various design and operational scenarios for both new and existing sort centers, ensuring their robustness, stability, scalability, and cost-effectiveness.

Our approach involves conceptualizing innovative data science solutions, leveraging optimization and machine learning platforms to analyze processes, identify and eliminate non-value-added steps, and enhance overall performance and efficiency.

We collaborate with various functional teams to test and pilot new hardware and software solutions.

BASIC QUALIFICATIONS:
- Master's or PhD with limited experience, or a Bachelor's degree in Statistics, Applied Mathematics, Operations Research, Economics, Engineering, or a related quantitative field with three years of experience as a Data Scientist.
- Proficiency in statistical analysis, data modeling, optimization, regression modeling, forecasting, time series analysis, data mining, financial analysis, and demand modeling.
- Experience applying diverse machine learning techniques and understanding the key parameters influencing their performance.
- Familiarity with statistical software such as R, Weka, SAS, SPSS.
- Proficiency in TABLEAU or similar web-based interfaces for creating graphic-rich, customizable plots, charts, and data maps.
- Ability to write SQL scripts for analysis and reporting (Redshift, SQL, MySQL).
- Experience with one or more programming languages (Python, R, Java, C++, MATLAB).
- Competence in processing, filtering, and presenting large datasets (ranging from 100K to millions of rows).

PREFERRED QUALIFICATIONS:
- Previous experience in a machine learning, data scientist, or optimization engineer role within a large technology organization.
- Familiarity with the processes utilized in Amazon's fulfillment and sortation network.
- Capability to develop experimental and analytical plans for data modeling processes, employing robust baselines to accurately determine cause-and-effect relationships.
- Experience in creating data-driven visualizations to illustrate an end-to-end system.
- Excellent written and verbal communication skills, with the ability to effectively engage with colleagues from diverse backgrounds in computer science, operations research, and business.
- Ability to thrive in a diverse team environment.


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