Data Scientist, Devices Global Logistics

We are seeking a creative, goal-oriented and highly technical person to join our Devices Global Logistics (DGL) Tech team. At DGL, we provide transportation and logistics services that deliver a disruptive value and make it easy for stakeholders to sell our products. We earn the trust of internal and external customers by being experts in our domain, providing the highest quality services at the lowest possible costs and being flexible.

We are looking for a Data Scientist who will grow their skills while enabling DGL mission through innovation, implementation, and support of our data solutions. This role is both strategic and hands-on. The ideal candidate will be an innovative problem solver with strong business acumen, leveraging techniques such as machine learning, statistics, forecasting and large language models to transform DGL logistics capabilities. You are excited to learn from and alongside seasoned scientists, engineers, and business leaders. You are an excellent communicator and effectively translate technical findings into business action.

The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, an ability to work in a fast-paced and ever-changing environment, and driven by a desire to innovate in this space.

Key job responsibilities
- Develop science models to enhance DGL systems, also forecast, classify, and detect anomalous patterns in supply chain and develop innovative models to solve these anomalies.
- Work with technical and non-technical customers across every step of the project life cycle.
- Collaborate with our product, data engineering, and software development teams to create production implementations for large-scale applications.
- Develop an understanding of key business metrics / KPIs and provide clear, compelling analysis that shapes the direction of our business.
- Simplify and automate business processes using smart tools (algorithms, AI, and science models).

Basic Qualifications

- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 2+ years of data scientist experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Bachelor's degree
- Experience applying theoretical models in an applied environment

Preferred Qualifications

- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company
- Experience with AWS services including S3, Redshift, Kendra, bedrock, Lambda, and EC2

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $125,500/year in our lowest geographic market up to $212,800/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.