Senior Data Scientist, UTR Optimization

Looking for your next challenge? North America Sort Centers (NASC) are experiencing growth and looking for a skilled, highly motivated Data Scientist to join the NASC Engineering Data, Product and Simulation Team.

The Sort Center network is the critical Middle-Mile solution in the Amazon Transportation Services (ATS) group, linking Fulfillment Centers to the Last Mile.

The experience of our customers is dependent on our ability to efficiently execute volume flow through the middle-mile network.

Key job responsibilities

The Data Scientist will design and implement solutions to address complex business questions using simulation. In this role, you will apply advanced analysis techniques and statistical concepts to draw insights from massive datasets, and create intuitive simulations and data visualizations.

You can contribute to each layer of a data solution you work closely with process design engineers, business intelligence engineers and technical product managers to obtain relevant datasets and create simulation models, and review key results with business leaders and stakeholders.

Your work exhibits a balance between scientific validity and business practicality.

On this team, you will have a large impact on the entire NASC organization, with lots of opportunity to learn and grow within the NASC Engineering team.

This role will be the first dedicated simulation expert, so you will have an exceptional opportunity to define and drive vision for simulation best practices on our team.

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 standards of data quality, security, and privacy.

About the team

NASC Engineering’s Product and Analytics Team’s sole objective is to develop tools for under the roof simulation and optimization, supporting the needs of our internal and external stakeholders (i.

e Process Design Engineering, NASC Engineering, ACES, Finance, Safety and Operations). We develop data science tools to evaluate what-if design and operations scenarios for new and existing sort centers to understand their robustness, stability, scalability, and cost-effectiveness.

We conceptualize new data science solutions, using optimization and machine learning platforms, to analyze new and existing process, identify and reduce non-value added steps, and increase overall performance and rate.

We work by interfacing with various functional teams to test and pilot new hardware / software solutions.

BASIC QUALIFICATIONS

Masters or PhD with limited experience, OR a Bachelors degree in Statistics, Applied Math, Operations Research, Economics, Engineering or a related quantitative field with three years of working experience as a Data Scientist

Experience with statistical analysis, data modeling, optimizations, regression modeling and forecasting, time series analysis, data mining, financial analysis, and demand modeling

Experience applying various machine learning techniques, and understanding the key parameters that affect their performance

Experience in Statistical Software such as R, Weka, SAS, SPSS

Proficiency with TABLEAU or other web based interfaces to create graphic-rich customizable plots, charts data maps etc.

Able to write SQL scripts for analysis and reporting (Redshift, SQL, MySQL)

Experience using one or more programming languages (Python, R, Java, C++, MATLAB)

Experience processing, filtering, and presenting large quantities (100K to Millions of rows) of data

PREFERRED QUALIFICATIONS

Previous experience in ML, data scientist or optimization engineer role with a large technology company

Familiarity with the processes used in Amazon fulfillment / sortation network

Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations

Experience in creating data driven visualizations to describe an end-to-end system

Excellent written and verbal communication skills. The role requires effective communication with colleagues from computer science, operations research and business backgrounds.

Ability to work on a diverse team or with a diverse range of coworkers