Sr. Data Scientist - Supply Chain
Company: Amazon.com, Inc.
Posted on: June 8, 2021
AWS Outcome Driven Engineering (ODE) is a new AWS engineering
organization chartered to build new AWS products by applying
Amazon's innovation mechanisms along with AWS digital technologies
to real world industry problems. We dive deep with industry leaders
to solve problems and unblock industries, enabling them to
capitalize on new digital business models. Simply put, our goal is
to use the skill and scale of AWS to make the benefits of a
connected world achievable for all businesses. Our team is focused
on saving hundreds of millions of dollars using cutting edge
science, machine learning, and scalable distributed software on the
Cloud that automates and optimizes inventory and shipments to
customers under the uncertainty of demand, pricing and supply.
We are looking for an experienced, passionate, hardworking and
analytical researcher to work with our partners and build new AWS
products. As a Data Scientist on the Outcome Development
Engineering team, you will collaborate directly with economists and
statisticians to produce modeling solutions, you will partner with
software developers and data engineers to build end-to-end data
pipelines and production code, and you will have exposure to senior
leadership as we communicate results and provide scientific
guidance to the business. You will analyze large amounts of
business data, automate and scale the analysis, and develop metrics
that will enable us to continually delight our customers worldwide.
As a successful data scientist, you are an analytical problem
solver who enjoys diving into data, is excited about investigations
and algorithms, can multi-task, and can credibly interface between
technical teams and business stakeholders. Your analytical
abilities, business understanding, and technical savvy will be used
to identify specific and actionable opportunities to solve existing
business problems and look around corners for future opportunities.
Your expertise in synthesizing and communicating insights and
recommendations to audiences of varying levels of technical
sophistication will enable you to answer specific business
questions and innovate for the future.
A day in the life
As a Sr. Data Scientist, you will solve real world problems by
analyzing large amounts of business data, defining new metrics and
business cases, designing simulations and experiments, creating ML
models, and collaborating with teammates in business, software, and
research. The successful candidate will have a strong quantitative
background and can thrive in an environment that leverages
statistics, machine learning, operations research, econometrics,
and business analysis.
- Working with product managers, software engineers, data
engineers, other data scientists, applied scientists to design,
develop, and evaluate highly innovative statistics and ML models to
drive efficiency through demand sensing, inventory optimization and
the design of new policies and incentives.
- Guide and establish scalable, efficient, automated processes
for large scale data analyses, model development, model validation
and model implementation
- Proactively seek to identify business opportunities and
insights and provide solutions to automate and optimize key
business processes and policies based on a broad and deep knowledge
of data, industry best-practices, and work done by other
- Collaborating with our dedicated software team to create
production implementations for large-scale data analysis and/or ML
- Developing and owning key business metrics / KPIs and providing
clear, compelling analysis that shapes the direction of our
Inclusive Team Culture
Our team has a developed a reputation for attracting,
developing, and retaining amazing talent from diverse backgrounds.
Yes, we do get to build really cool services and work closely with
customers, but we also think a big reason for our diversity is the
inclusive and welcoming culture we try to cultivate every day.
We're looking for a new teammate who is enthusiastic, empathetic,
curious, motivated, reliable, and able to work effectively with a
diverse team of peers; someone who will help us amplify the
positive & inclusive team culture we've been building.
In addition to Seattle - Palo Alto, Dallas, Atlanta, the Boston
Metro area, and other East Coast locations in North America will
also be given consideration.
- Master's degree in a highly quantitative field: Machine
Learning, AI, Computer Science, Statistics, Mathematics,
Operational Research, etc.
- 4+ years of hands-on industry experience in predictive modeling
and analysis, causal inference, or multivariate statistics, as an
ML engineer or data scientist role, applying various ML techniques,
and deep understanding the key parameters that affect their
- Strong Analytical skills - has ability to scope out business
problems to be solved, start from ambiguous problem statements,
identify and access relevant data, make appropriate assumptions,
perform insightful analysis and draw conclusion relevant to the
- Proficient with Python and data manipulation/analysis libraries
such as Scikit-learn and Pandas for analyzing and modeling
- Experienced in using multiple data science methodologies to
solve complex business problems (e.g. statistical analysis,
research science, machine learning and deep learning techniques,
data modeling, regression modeling, financial analysis, demand
- Experience with managing large and disparate data sources
- Excellent communication skills. Proven ability to communicate
verbally and in writing to technical peers and business teams,
educating them about our systems, as well as sharing insights and
- A PhD degree in a highly quantitative field (Machine Learning,
AI, Computer Science, Statistics, Mathematics, Operational
- 8+ years' experience in a ML or Data Scientist role with a
large technology company.
- Extensive knowledge and practical experience in several of the
following areas: machine learning, statistics, NLP, deep learning,
recommendation systems, information retrieval.
- Skilled with Java, C++, or other similar programming
- Functional knowledge of AWS platforms such as S3, Glue, Athena,
- Advanced knowledge and expertise with Data modeling skills,
Advanced SQL with Oracle, MySQL, Redshift and Columnar
- Knowledge of professional software engineering practices & best
practices for the full software development life cycle, including
coding standards, code reviews, source control management, build
processes, testing, and operations.
- Track record of dealing well with ambiguity, prioritizing
needs, and delivering results in a dynamic environment
Keywords: Amazon.com, Inc., Arlington , Sr. Data Scientist - Supply Chain, Other , Arlington, Virginia
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