Data Scientist, Indirect Supply Chain

Job description

DESCRIPTION

Amazon WW Operations Organization is seeking an experienced Data Scientist to help optimize Amazon's indirect supply chain.

The Indirect Supply Chain Optimization REinvent (ISCORE) team develops and supports technology solutions to optimize the indirect supply chain, and the processes associated with managing and operating it. Our focus includes tracking, inventory management, ordering and reverse logistics systems for consumable and reusable non-inventory items in support of customer package deliveries.

In this role, you will be a technical expert with significant scope and impact. You will work with Program Managers, Business Intelligence Engineers, Data Engineers, Software Engineers, and other Data Scientists, to build ML models to optimize Amazon’s indirect supply chain. The successful Data Scientist will have extreme bias for action needed in a startup environment, with outstanding leadership skills, proven ability to build and manage medium-scale modeling projects, identify data requirements, build methodology and tools that are statistically grounded.

We are seeking someone who can thrive in a fast-paced, high-energy and fun work environment where we deliver value incrementally and frequently. We value highly technical people who know their subject matter deeply and are willing to learn new areas. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career.

PREFERRED QUALIFICATIONS

· PhD in Statistics, Mathematics, Business Analytics, or related quantitative discipline.
· Experience applying forecasting and data mining techniques in an industrial setting.
· Experience with processing, analyzing, and modeling with geo-spatial data
· Demonstrable experience in leveraging analytics to generate business value especially in related business sectors such as Logistics and Supply Chains, Transportation, and Engineering.
· Fluency in a scripting or computing language (e.g. Python, R, Java, C++, etc.)
· Experience with big data: extraction, processing, filtering, and presenting large data quantities (100K to Millions of rows) via AWS technologies, SQL, and data pipelines
· Experience with agile/scrum methodologies and its benefits of keeping scientists on track and iteratively delivering results.
· Familiarity with Logistics/Supply Chain, or related Businesses.
· Expert knowledge of SQL

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, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Desired profile

BASIC QUALIFICATIONS

· Masters in Statistics, Mathematics, Business Analytics, or related quantitative discipline.
· Deep understanding of regression modeling, forecasting techniques, time series analysis, machine-learning concepts such as supervised and unsupervised learning, classification, random forest, etc.
· Experience in developing machine-learning algorithms, statistical and mathematical optimization models, and simulation and visualization tools
· Familiarity with managing disparate data sets; including, building and maintaining data flows and pipelines
· Experience with SQL and at least one scripting language (preferable Python)
· Exposure to big data: extraction, processing, filtering, and presenting large data quantities (100K to Millions of rows) via AWS technologies, SQL, and data pipelines
· Industry experience in defining and building metrics, performing business analysis, and quantifying decisions through the utilization of data
· Ability to communicate technical concepts and solutions at a level appropriate for technical and non-technical audiences