Data Scientist, Infra Supply Chain Automation

Key Skills

Java Programming, Python Programming, SQL, AWS, PowerBI, MATLAB Programming, R Programming, Amazon RedShift, Amazon EMR, Amazon RDS, AWS Sagemaker, Amazon Simple Storage Service (S3), SAS, Data Engineering, ETL frameworks

Job Description

The AWS Infrastructure Planning group is responsible for planning and coordinating a complex, multi-tier supply chain that's delivers capacity for all AWS services. This includes data center setup, equipment purchase, installation and operation of servers with power and cooling, inventory management and other such decisions.

We're building a new suite of tools to automate all AWS supply chain planning, with a broad charter that involves inventory optimization, placement, vendor allocation, transition management, lead time predictions, and more. We are responsible for ensuring that the AWS cloud remains elastic for its customers by taking care of all of the back-end complexity, enabling our infrastructure to stay ahead of our rapid growth.

We are looking for a highly motivated, analytical and detail-oriented candidate to help build scalable prescriptive business analytics solutions that supports our Supply Chain Operating System (known as SC.os) Planning organization. You will be part of the SC.os Data Science team working primarily with SDEs, Product Managers, Applied and Data Scientists, Directors, Sr. Managers to achieve our goals.

In this role, you will apply advanced analysis technique and statistical concepts to draw insights from massive datasets, create intuitive data visualizations, and build scalable machine learning models. You are a pragmatic generalist. You can contribute to each layers of a data solution – you work closely with business intelligence engineers and product managers to obtain relevant datasets and prototype predictive analytic models, you team up with data engineers and software development engineers to implement data pipeline to productionize your models, and review key results with business leaders and stakeholders. Your work exhibits a balance between scientific validity and business practicality.

Key job responsibilities

In this role, you will apply advanced analysis technique and statistical concepts to draw insights from massive datasets, create intuitive data visualizations, and build scalable models. You are a pragmatic generalist. You can contribute to each layers of a data solution – you work closely with software engineers, data engineers and product managers to obtain relevant datasets and prototype predictive analytic models, you team up with data engineers and software development engineers to implement data pipeline to productionize your models, and review key results with business leaders and stakeholders. Your work exhibits a balance between scientific validity and business practicality.

To be successful in this role, you must be able to turn ambiguous business questions into clearly defined problems, develop quantifiable metrics and robust machine learning models from imperfect data sources, and deliver results that meet high standards of data quality, security, and privacy.

• Analyze data from AWS Supply Chain and Fulfillment planning outcomes, communicate insights and recommendations to product, engineering, and business teams
• Interview stakeholders to gather business requirements and translate them into concrete requirement for data science projects
• Build models that forecast growth and incorporate inputs from product, engineering, finance and marketing partners
• Apply data science techniques to automatically identify trends, patterns, and frictions of customer interaction and retention
• Work with data engineers and software development engineers to deploy models and experiments to production
• Identify and recommend opportunities to automate systems, tools, and processes.

BASIC QUALIFICATIONS

• Bachelor's Degree
• 5+ years of experience with data scripting languages (e.g SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
• 4+ years working as a Data Scientist.

PREFERRED QUALIFICATIONS

• Master's degree or Ph.D in Computer Science, Mathematics, Statistics, related technical field
• 5+ years working as a Data Scientist or related fields
• 2+ years of experience as Tech Lead among data scientists
• Strong communication and presentation skills necessary to build effective working relationships and positively influence decision making
• Strong business acumen and product sense
• Detailed knowledge of data warehouse technical architecture, infrastructure components, ETL and reporting/BI tools and environments
• Experience with large datasets (billions of rows)
• Experience with AWS technologies (SageMaker, Redshift, RDS, S3, EMR, 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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.