Data Scientist II, Demand Forecasting

Amazon; New York (NY); On-site; USD 125,000 - 213,000; Full time

Job summary

Join a forward-thinking company as a Data Scientist, where you will optimize a complex global supply chain through advanced data analysis and innovative modeling techniques. This role is pivotal in forecasting demand for millions of products, using your analytical skills to influence key business decisions. You will collaborate with product managers and engineering teams to develop agile model solutions and automate processes, ensuring accurate predictions that delight customers. If you're passionate about data and thrive in a dynamic environment, this opportunity is perfect for you.

Qualifications

• 3+ years of experience with data querying and scripting languages.
• 2+ years of experience in a data scientist role.
• Experience in machine learning and statistical modeling.

Responsibilities

• Collaborate with teams to design and implement model solutions.
• Develop models for ongoing demand measurements.
• Interpret data and make actionable recommendations.

Skills

SQL

Python

Statistical Analysis

Machine Learning

Data Analysis

Causal Inference

Education

Bachelor's Degree

Tools

TensorFlow

PyTorch

Keras

R

SAS

Matlab

Job description

Job ID: 2971353 | Amazon.com Services LLC

Amazon has the world’s most complex supply chain: we fulfill global demand for hundreds of millions of products at lightning fast delivery speeds. We need your skills to optimize our supply chain, with the end goal of delighting our customers. A core part of the supply chain operations is Demand Forecasting: We forecast the demand of tens of millions of products. These forecasts are used to make many decisions, such as automatically order hundreds of millions worth of inventory, decide where to place that inventory, and establish labor plans for hundreds of warehouses.

The Demand Forecasting Team is looking for an analytical and technically skilled Data Scientist to join our team. This position will be responsible for developing and supporting best-in-class data science methodologies and building models to address ambiguous forecasting questions. The Data Scientist needs to be familiar with deriving causal inferences using observational data and able to model variations related with demand prediction, out of stock, seasonality, and different lead times and spans. Upon completion of statistical analysis, the Data Scientist needs to communicate measurement results to stakeholders by translating technical framework to business-oriented insights.

This role requires an individual with excellent analytical abilities as well as business acumen. The successful candidate will be a self-starter comfortable with ambiguity, with attention to detail, vocally self-critical, an ability to work in a fast-paced and ever-changing environment. They recognize that the true measure of the success of the work product is based on the business impact the findings have had.


Key job responsibilities
- Collaborate with product managers and deep learning science and engineering teams to design and implement agile model solutions for Amazon demand core models
- Develop edge case agile models for on-going demand measurements toward the end goal of accurately predicting customer demand for millions of products world-wide
- Use large datasets or experiments to make causal inferences or predictions
- Work with engineers to automate science analysis processes and build scalable measurement solutions
- Interpret data, write reports, and make actionable recommendations
- Keys to success in this role include exceptional analytics, statistics, judgment, and communication skills. The candidate will need to be able to extract insights from data and be able to clearly communicate appropriate triggers and actions

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 a ML or data scientist role with a large technology company
- Proven experience designing, implementing, and optimizing neural network architectures for complex problems, particularly in time series modeling.
- Proficiency with modern deep learning frameworks such as TensorFlow, PyTorch, or Keras.

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.

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