DESCRIPTION
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.
The Data Scientist I will design and implement solutions to address complex business questions using advanced statistical and machine learning techniques, experimentation, and big data. In this role, you will build scalable ML models, apply advanced analysis technique and statistical concepts to draw insights from massive datasets, and create intuitive science models and data visualizations. You can contribute to each layers of a data solution – you will work closely with business intelligence engineers and product managers to obtain relevant datasets and prototype predictive analytic models, and implement data pipeline to productionize your models, and review key results with business leaders and stakeholders. Your work exhibits a balance between scientific validity and business practicality.
To be successful in this role, you must be able to turn ambiguous business questions into clearly defined problems, develop quantifiable metrics and robust machine learning models from imperfect data sources, and deliver results that meet high standards of data quality, security, and privacy.
Key job responsibilities
- Development of scalable data science solutions catering to volume and cube forecasting for NASC Sales and Operation Planning Team.
- Working closely with Network Planners, Product Managers, Data Scientists and various planning teams to drive business decisions and alignment with business stakeholders.
- Development of scalable data science solutions to audit and optimize our NASC network.
- Development and execution of analytical tools to model our transportation network.
- Contribute to the strategy for network design, prioritize technical and operational initiatives, evaluate and set stakeholders expectations.
We are open to hiring candidates to work out of one of the following locations:
Bellevue, WA, USA | Nashville, TN, USA
BASIC QUALIFICATIONS
- Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- Experience with data scripting languages (e.g. SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
PREFERRED QUALIFICATIONS
- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- Experience as a data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources
- Experience or education in Supply chain Domain, Network Planning or Logistics.
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $97,500/year in our lowest geographic market up to $206,800/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
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