Applied Scientist - Forecasting & Risk Modeling, Amazon Transportation
Santa Clara, California, USA
⚠️ We'll shut down after Aug 1st - try foo🦍 for all jobs in tech ⚠️
Full Time Senior-level / Expert USD 150K - 260K
Amazon.com
Free shipping on millions of items. Get the best of Shopping and Entertainment with Prime. Enjoy low prices and great deals on the largest selection of everyday essentials and other products, including fashion, home, beauty, electronics, Alexa...
mmPROS Surface Research Science seeks an exceptional Applied Scientist with expertise in forecasting and risk modeling to optimize Amazon's middle mile transportation network, the backbone of its logistics operations. Amazon's middle mile transportation network utilizes a fleet of semi-trucks, trains, and air planes to transport millions of packages per day as well as other freight between warehouses, vendor facilities, and customers, on time and at low cost.
The mmPROS Surface Research Science team delivers innovation, models, algorithms, and other scientific solutions to efficiently plan and operate the middle mile surface (truck and rail) transportation network. The team focuses on large-scale problems in vehicle route planning, capacity procurement, network design, forecasting, and equipment re-balancing. Your role will be to build innovative forecasting, risk quantification, and other machine learning models to decide the optimal long-term and short-term strategy for truck capacity procurement and other planning problems.
Your models will impact business decisions worth billions of dollars and improve the delivery experience for millions of customers. You will operate as part of a team of innovative, experienced scientists working on machine learning and optimization problems, and you will work in close collaboration with partners across product, engineering, business intelligence, and operations.
Key job responsibilities
- Design, develop, and implement forecasting models, risk models, and other machine learning models to inform our hardest planning decisions.
- Implement machine learning and risk models in Amazon's production software.
- Lead and partner with product, engineering, and operations teams to drive modeling and technical design for complex business problems.
- Lead complex modeling and data analyses to aid management in making key business decisions and set new policies.
- Write documentation for scientific and business audiences.
About the team
This role is part of mmPROS Surface Research Science. Our mission is to build the most efficient and optimal transportation network on the planet, using our science and technology as our biggest advantage. We aim to leverage cutting edge technologies in optimization, operations research, and machine learning to grow our businesses and solve Amazon's unique logistical challenges.
Scientists in the team work in close collaboration with each other and with partners across product, software engineering, business intelligence, and operations. They regularly interact with software engineering teams and business leadership.
- 3+ 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
- Experience with large scale distributed systems such as Hadoop, Spark etc.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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.
The mmPROS Surface Research Science team delivers innovation, models, algorithms, and other scientific solutions to efficiently plan and operate the middle mile surface (truck and rail) transportation network. The team focuses on large-scale problems in vehicle route planning, capacity procurement, network design, forecasting, and equipment re-balancing. Your role will be to build innovative forecasting, risk quantification, and other machine learning models to decide the optimal long-term and short-term strategy for truck capacity procurement and other planning problems.
Your models will impact business decisions worth billions of dollars and improve the delivery experience for millions of customers. You will operate as part of a team of innovative, experienced scientists working on machine learning and optimization problems, and you will work in close collaboration with partners across product, engineering, business intelligence, and operations.
Key job responsibilities
- Design, develop, and implement forecasting models, risk models, and other machine learning models to inform our hardest planning decisions.
- Implement machine learning and risk models in Amazon's production software.
- Lead and partner with product, engineering, and operations teams to drive modeling and technical design for complex business problems.
- Lead complex modeling and data analyses to aid management in making key business decisions and set new policies.
- Write documentation for scientific and business audiences.
About the team
This role is part of mmPROS Surface Research Science. Our mission is to build the most efficient and optimal transportation network on the planet, using our science and technology as our biggest advantage. We aim to leverage cutting edge technologies in optimization, operations research, and machine learning to grow our businesses and solve Amazon's unique logistical challenges.
Scientists in the team work in close collaboration with each other and with partners across product, software engineering, business intelligence, and operations. They regularly interact with software engineering teams and business leadership.
Basic Qualifications
- 3+ 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
- 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 an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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.
Job stats:
0
0
0
Category:
Data Science Jobs
Tags: Business Intelligence Computer Science Deep Learning Distributed Systems Engineering Hadoop Java Machine Learning Mathematics ML models MXNet NumPy Perl PhD Python R Research Robotics Scikit-learn SciPy Spark Statistics TensorFlow
Perks/benefits: Career development Equity / stock options
Region:
North America
Country:
United States
More jobs like this
Explore more career opportunities
Find even more open roles below ordered by popularity of job title or skills/products/technologies used.
Sr. Data Engineer jobsPower BI Developer jobsPrincipal Data Engineer jobsData Scientist II jobsBI Developer jobsStaff Data Scientist jobsPrincipal Software Engineer jobsStaff Machine Learning Engineer jobsDevOps Engineer jobsData Science Intern jobsJunior Data Analyst jobsSoftware Engineer II jobsAI/ML Engineer jobsStaff Software Engineer jobsData Science Manager jobsData Manager jobsLead Data Analyst jobsData Analyst Intern jobsData Specialist jobsSr. Data Scientist jobsBusiness Data Analyst jobsBusiness Intelligence Analyst jobsData Governance Analyst jobsData Engineer III jobsSenior Backend Engineer jobs
Consulting jobsMLOps jobsAirflow jobsOpen Source jobsKafka jobsEconomics jobsKPIs jobsGitHub jobsLinux jobsJavaScript jobsTerraform jobsPostgreSQL jobsRAG jobsPrompt engineering jobsBanking jobsStreaming jobsData Warehousing jobsScikit-learn jobsNoSQL jobsClassification jobsRDBMS jobsComputer Vision jobsPhysics jobsdbt jobsHadoop jobs
Pandas jobsScala jobsGoogle Cloud jobsGPT jobsData warehouse jobsR&D jobsLangChain jobsMicroservices jobsBigQuery jobsCX jobsELT jobsOracle jobsDistributed Systems jobsScrum jobsLooker jobsReact jobsIndustrial jobsPySpark jobsRedshift jobsJira jobsOpenAI jobsRobotics jobsSAS jobsUnstructured data jobsSalesforce jobs