What are the responsibilities and job description for the Sr. Applied Scientist, Last Mile Science position at Amazon?
DESCRIPTION
Have you ever ordered a product on Amazon and when that box with the smile arrived you wondered how it got to you so fast? Have you wondered where it came from and how much it cost Amazon to deliver it to you? If so, the WW Amazon Logistics, Business Analytics team is for you. We manage the delivery of tens of millions of products every week to Amazon’s customers, achieving on-time delivery in a cost-effective manner.
We are looking for an enthusiastic, customer obsessed, Sr. Applied Scientist with good analytical skills to help manage projects and operations, implement scheduling solutions, improve metrics, and develop scalable processes and tools. The primary role of an Operations Research Scientist within Amazon is to address business challenges through building a compelling case, and using data to influence change across the organization. This individual will be given responsibility on their first day to own those business challenges and the autonomy to think strategically and make data driven decisions. Decisions and tools made in this role will have significant impact to the customer experience, as it will have a major impact on how the final phase of delivery is done at Amazon.
Ideal candidates will be a high potential, strategic and analytic graduate with a PhD in (Operations Research, Statistics, Engineering, and Supply Chain) ready for challenging opportunities in the core of our world class operations space. Great candidates have a history of operations research, and the ability to use data and research to make changes.
This role requires robust program management skills and research science skills in order to act on research outcomes. This individual will need to be able to work with a team, but also be comfortable making decisions independently, in what is often times an ambiguous environment.
Responsibilities may include:
- Develop input and assumptions based preexisting models to estimate the costs and savings opportunities associated with varying levels of network growth and operations
- Creating metrics to measure business performance, identify root causes and trends, and prescribe action plans
- Managing multiple projects simultaneously
- Working with technology teams and product managers to develop new tools and systems to support the growth of the business
- Communicating with and supporting various internal stakeholders and external audiences
BASIC QUALIFICATIONS
- 10 years of building machine learning models or developing algorithms for business application experience
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, or Master's degree and 10 years of industry or academic research experience
- Knowledge of programming languages such as C/C , Python, Java or Perl
- Experience with neural deep learning methods and machine learning
PREFERRED QUALIFICATIONS
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- 15 years of relevant, broad research experience after PhD degree or equivalent.
- Deep expertise in Machine Learning
- Proficiency in programming for algorithm and code reviews.
- Strong core competency in mathematics and statistics.
- Track record of successful projects in algorithm design and product development.
- Publications at top-tier peer-reviewed conferences or journals.
- Strong prior experience with mentorship and/or management of senior scientists and engineers.
- Thinks strategically, but stays on top of tactical execution.
- Exhibits excellent business judgment; balances business, product, and technology very well.
- Effective verbal and written communication skills with non-technical and technical audiences.
- Experience working with real-world data sets and building scalable models from big data.
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
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.
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 $150,400/year in our lowest geographic market up to $260,000/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.
Salary : $150,400 - $260,000
